{
 "name": "The Corpus of AI Cliches",
 "version": "1.8",
 "generated": "2026-07-18",
 "scoring": {
  "strength_score": "0-100 composite detection-strength. Published per-term evidence used where available: detector scores (Your AI Slop Bores Me Hall of Shame), GPTZero AI Vocabulary frequency ratios, peer-reviewed ratios (Kobak, Juzek & Ward, Liang, Ward), and EQ-Bench / antislop slop-list rankings; otherwise banded by confidence tier (strong=75, moderate=50, context=30).",
  "confidence": "red=strong tell, orange=moderate tell, yellow=context-dependent (overuse only).",
  "example": "Optional illustrative sentence(s) showing the pattern. Populated for structural entries (sentence patterns, hook openers, rhetorical moves, formatting tells).",
  "study_ratio": "Peer-reviewed measured value, populated only where one exists. metric 'r'=frequency ratio (2024 vs expected); metric 'delta'=excess frequency gap (absolute prevalence increase).",
  "note": "Optional observed-frequency context (e.g. name dominance in controlled prompt tests).",
  "names_caveat": "Individual names are weak evidence alone (real people share them). They are tells in clusters, in AI-generation contexts, or for distinctive fantasy coinages. Only 'Elara' and a few full-name personas approach diagnostic on their own.",
  "study_source": "Kobak et al. 2024, arXiv:2406.07016 (14M PubMed abstracts)",
  "lifecycle": "Tell lifecycle, orthogonal to confidence (Gibbs 2026). hard_evidence=machine artifact, proof of tooling; live=still statistically reliable on current-model output; fading=real in 2023-24, publicized to death and now declining; red_herring=patched out or inverted (e.g. em dash: models now underuse it, so its ABSENCE is the newer signal). The density scorer weights matches by lifecycle so decayed vocabulary no longer inflates the score."
 },
 "study_headline_figures": {
  "delves_frequency_ratio": 25.2,
  "showcasing_frequency_ratio": 9.2,
  "underscores_frequency_ratio": 9.1,
  "potential_excess_gap": 0.041,
  "findings_excess_gap": 0.027,
  "crucial_excess_gap": 0.026,
  "min_share_2024_pubmed_abstracts_llm_processed": "at least 10%",
  "source": "Kobak et al. 2024, arXiv:2406.07016 (14M PubMed abstracts)"
 },
 "entry_count": 758,
 "entries": [
  {
   "term": "delve",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "fading",
   "strength_score": 99,
   "example": null,
   "study_ratio": 25.2,
   "study_metric": "r",
   "study_measured_form": "delves",
   "study_source": "Kobak et al. 2024, arXiv:2406.07016 (14M PubMed abstracts)",
   "note": null
  },
  {
   "term": "tapestry",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "red",
   "lifecycle": "fading",
   "strength_score": 97,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "it's important to note",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 96,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "multifaceted",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 95,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "landscape",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 94,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "nuanced",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 93,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "pivotal",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "red",
   "lifecycle": "fading",
   "strength_score": 92,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "realm",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 91,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Elara",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (female)",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 90,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "seehuhn.de 2026 (100-prompt Claude test); Namerology 2025 Name of the Year (Elara)",
   "note": "Namerology 2025 'Name of the Year'; treated by teachers as a dead giveaway in fiction"
  },
  {
   "term": "leverage",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 90,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "underscore",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 89,
   "example": null,
   "study_ratio": 9.1,
   "study_metric": "r",
   "study_measured_form": "underscores",
   "study_source": "Kobak et al. 2024, arXiv:2406.07016 (14M PubMed abstracts)",
   "note": null
  },
  {
   "term": "Marcus Chen",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 88,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "seehuhn.de 2026 (100-prompt Claude test); Namerology 2025 Name of the Year (Elara)",
   "note": "100/100 for 'a software developer' (Claude Sonnet 4.5; seehuhn 2026)"
  },
  {
   "term": "embark on a journey",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 87,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "holistic approach",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 86,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Elara Voss",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 85,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "it's worth noting",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 84,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "streamline",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 83,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Sarah Chen",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "foster",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "robust",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "red",
   "lifecycle": "fading",
   "strength_score": 81,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Elena Vasquez",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 80,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "resonate",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 80,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "elevate",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 79,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "As an AI language model",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "hard_evidence",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "As of my last knowledge update",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "certainly! here's",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I cannot fulfill this request",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I do not have access to real-time",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I don't have personal opinions",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I don't have the ability to",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I'd be happy to assist you with that",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I'm just an AI",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I'm sorry, but I cannot",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "please note that I am an AI",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "don't hesitate to reach out",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I hope this email finds you well",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I hope this message finds you well",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I hope you're doing well",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I trust this email finds you well",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I wanted to reach out",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I'm reaching out because",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Email slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Agree?",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "And honestly? That's okay.",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Here's why that matters:",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "I'll say it louder for the people in the back",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Let that sink in",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Let's dive in 🧵",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Read that again",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Thoughts?",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Bolded-term bullet (**Term:** restated definition)",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "- **Scalability:** The system is highly scalable and scales to meet demand.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Emoji as structural scaffolding (rocket/bulb/check bullets)",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "🚀 Faster shipping\n💡 Smarter decisions\n✅ Happier customers",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Kira Voss",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "seehuhn.de 2026 (100-prompt Claude test); Namerology 2025 Name of the Year (Elara)",
   "note": "dominant 'spaceship pilot' name (~31% of 100; seehuhn 2026)"
  },
  {
   "term": "Challenges-and-prospects pivot (Despite challenges, opportunities abound)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Despite these challenges, the opportunities ahead are immense.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Compulsive hedging / false balance",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "It depends on a variety of factors, and both sides make valid points.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Editorializing markers (it is worth noting / as we will see)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "It is worth noting that this trend shows no signs of slowing.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Significance inflation (sentence-level)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "This represents a fundamental shift in how we think about work.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Sycophantic flattery (\"Great question!\", \"You're absolutely right!\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Great question! You're absolutely right to think about it this way.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Throat-clearing openers (Let me be clear / Before we dive in)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Before we dive in, let me be clear about one important thing.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Vague authority attribution (experts argue / studies suggest)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Experts argue that remote work is here to stay.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Community frame (\"Whether you're a founder, a marketer, or...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Whether you're a founder, a freelancer, or a Fortune 500 exec, this applies to you.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Reveal setup (\"Here's the thing...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Here's the thing nobody tells you about scaling a team.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Temporal-landscape opener (\"In today's landscape...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "In today's fast-paced digital landscape, standing out is harder than ever.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "World-state opener (\"In a world where...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "In a world where attention is the scarcest resource, clarity wins.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "\"No X. No Y. No Z.\" construction",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "No fluff. No filler. No wasted time.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "AI Sentence DNA arc (opening -> expansion -> contrast -> resolution)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "AI is reshaping work. It automates the routine. But it's not about replacement — it's about leverage. The takeaway? Adapt now.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Choppy fragment pairs (\"All the X. None of the Y.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "All the flavor. None of the calories.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Contrastive negation: \"It's not just X, it's Y\"",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "It's not just about writing faster. It's about writing better.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "False ranges (\"From X to Y\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "From startups to Fortune 500s, everyone is rethinking work.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Imperative-then-payoff (\"Stop doing X. Start doing Y.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Stop chasing tactics. Start building systems.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Motivational cadence (claim -> expansion -> imperative payoff)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Most people wait for permission. You don't need it. The choice is yours.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Negative parallelism: \"not only X but also Y\"",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "This not only saves time but also reduces errors.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Staccato one-word sentences (\"Simple. Effective. Easy.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Our approach? Simple. Effective. Proven.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "a growing body of research",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "has garnered significant attention",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "paving the way for",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "sheds light on",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "a gateway to",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "at the forefront of",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "bring to the table",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
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   "note": null
  },
  {
   "term": "in a nutshell",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "low-hanging fruit",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "move the needle",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "take it to the next level",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
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   "study_source": null,
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  {
   "term": "think outside the box",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
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  {
   "term": "thought leader",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
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   "strength_score": 75,
   "example": null,
   "study_ratio": null,
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   "study_measured_form": null,
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  {
   "term": "when all is said and done",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
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   "study_source": null,
   "note": null
  },
  {
   "term": "a key takeaway is",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
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  {
   "term": "food for thought",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
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  {
   "term": "last but not least",
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   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
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  {
   "term": "let's unpack",
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   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
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  {
   "term": "speaks volumes",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
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   "strength_score": 75,
   "example": null,
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  {
   "term": "this highlights the fact that",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "red",
   "lifecycle": "live",
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   "example": null,
   "study_ratio": null,
   "study_metric": null,
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   "note": null
  },
  {
   "term": "this underscores the importance of",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
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  {
   "term": "to put it simply",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
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   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
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  {
   "term": "Absolutely!",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
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  {
   "term": "As we move forward",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
   "confidence": "red",
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   "example": null,
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  {
   "term": "At the end of the day",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
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   "example": null,
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  {
   "term": "Certainly!",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
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  {
   "term": "Feel free to reach out",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
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   "example": null,
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  {
   "term": "Great question!",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
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  {
   "term": "Happy [verb]-ing!",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
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   "lifecycle": "live",
   "strength_score": 75,
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   "term": "Theron",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (male)",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Blackwood",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Castellano",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Chen",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Kincaid",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Kowalski",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Marchetti",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Nightshade",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Sterling",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Thorne",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Vance",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Vasquez",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Vex",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Eleanor Vance",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Elena Rodriguez",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Elena Voss",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Mara Chen",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Michael Chen",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Full-name personas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Agreement mirroring (flips position to match the reader)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "You make an excellent point — I completely agree with your revised take.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Assumed consensus (\"As we all know\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "As we all know, first impressions matter.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Both-sides non-answer (lists pros and cons, won't decide)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "There are compelling arguments on both sides, and ultimately it's up to you.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Clean summary close (every paragraph bows itself off)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "In summary, the key is balance — a theme we'll return to throughout.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Definition-first opening (\"X, at its core, is...\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Leadership, at its core, is about trust.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Disclaimer stacking",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Please note this is general information and not professional advice; always consult an expert.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Empathy preface (\"I understand this can be frustrating\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "I understand this can be frustrating, and that's completely valid.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Faux-Socratic mid-essay question (\"But what does this really mean?\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "But what does this really mean for your business? Let's break it down.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Generic, unfalsifiable evidence (a leading firm)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "A leading financial-services company saw dramatic results.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Manufactured stakes / urgency",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The decisions you make today will define the next decade of your life.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "No intellectual wrong turns (frictionless thesis)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The argument arrives fully formed, never doubting or revising itself.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Numbered key-takeaways wrap",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Key takeaways: 1) Start small. 2) Stay consistent. 3) Measure everything.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Over-signposting (\"First... Second... Finally...\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "First, let's define the problem. Second, let's explore causes. Finally, solutions.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Reassurance close (\"You've got this!\")",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Remember, every expert was once a beginner. You've got this!",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Restating the prompt as the opening line",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Writing a great cover letter is an important step in any job search.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Symmetric / uniform development",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Each of the three options is explored in equal, identically structured depth.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Candor opener (\"Let's be honest...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Let's be honest: most onboarding emails go unread.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Confession opener (\"I used to think X. I was wrong.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "I used to think hustle was everything. I was wrong.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Contrarian opener (\"Most people believe X. They're wrong.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Most people think more features win. They're wrong.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Curiosity hook (\"Have you ever wondered...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Have you ever wondered why some teams ship twice as fast?",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Direct-imperative opener (\"Stop doing X.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Stop optimizing your morning routine. Start optimizing your decisions.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Empathy opener (\"If you've ever struggled with...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "If you've ever struggled to stay focused, you're not alone.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Statistic opener (\"Studies show that X% of...\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Studies show that 90% of startups fail within their first five years.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Urgency frame (\"The window for X is closing.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The window for early adopters is closing fast.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "\"Enter [X].\" dramatic introduction",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Teams needed a faster way to ship. Enter automation.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "\"X. Y. Z.\" three-fragment payoff line",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Build. Measure. Learn.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Anaphora (same opening word repeated across sentences)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "They doubted the plan. They questioned the timing. They were wrong.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Aphorism stacking (abstract declaratives in a row)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Clarity is speed. Less is more. The simplest version usually wins.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Bold-hook opener + short punchy lines (social-post shape)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "I lost my biggest client.\n\nThen I learned the lesson that changed everything.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Colon reveal (\"The result: X.\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "We cut the process in half. The result: happier customers.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Complex prepositional padding (\"taking into account\", \"in the context of\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "In the context of modern teams, and taking into account remote work, alignment matters.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Copulative avoidance (serves as / stands as / represents)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The bridge serves as a connection between the two districts.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Hedge-then-assert",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "While there's no single answer, one thing is clear: consistency wins.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Paradox line (\"The more you X, the less you Y\")",
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   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Nguyen",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Patel",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Reed",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Rodriguez",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Elegant variation (renaming the same referent)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "The company grew. The firm expanded. The organization thrived.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Relentless second person",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "You might be wondering. You'll find. Your journey starts here.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Tacked-on call to action",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "So go ahead — take the first step toward a better workflow today.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Rhetorical-question opener",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "What if everything you knew about productivity was wrong?",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "Sentence-initial And/But for manufactured momentum",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "And that's when everything changed. But it wasn't easy.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "playbook",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "at the same time",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "in other words",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Connective / transition phrases",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "tends to",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hedges & qualifiers",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "findings",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": 0.027,
   "study_metric": "delta",
   "study_measured_form": "findings",
   "study_source": "Kobak et al. 2024, arXiv:2406.07016 (14M PubMed abstracts)",
   "note": null
  },
  {
   "term": "potential",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": 0.041,
   "study_metric": "delta",
   "study_measured_form": "potential",
   "study_source": "Kobak et al. 2024, arXiv:2406.07016 (14M PubMed abstracts)",
   "note": null
  },
  {
   "term": "blend",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "discern",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "emulate",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "interpret",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "ponder",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "scaffold",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": null
  },
  {
   "term": "watershed moment",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Significance-inflation formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Significance-inflation phrase flagged alongside pivotal / turning point. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "valuable insights",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 78,
   "example": null,
   "study_ratio": 468,
   "study_metric": "r",
   "study_measured_form": "provide valuable insights",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "AI declares its own analysis important unprompted; 468x more frequent in AI text per GPTZero. Also in Wikipedia superficial-analysis markers."
  },
  {
   "term": "diverse array",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Padding collocation; sibling of a-wide-range-of. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "focal point",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Artificially centers minor subjects (has become a focal point of). Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "left an indelible mark",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Significance-inflation formulas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": null,
   "study_ratio": 317,
   "study_metric": "r",
   "study_measured_form": "left an indelible mark",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "Legacy-inflation formula in AI biography and history text; 317x more frequent in AI per GPTZero."
  },
  {
   "term": "in the heart of",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Tourism-brochure vocabulary",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Travel-brochure framing, usually paired with nestled. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "unwavering commitment",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 80,
   "example": null,
   "study_ratio": 202,
   "study_metric": "r",
   "study_measured_form": "an unwavering commitment",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "Near-obligatory in AI about-us and tribute copy; 202x more frequent in AI per GPTZero."
  },
  {
   "term": "active social media presence",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Encyclopedia & bio slop",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Idiosyncratic post-2024 AI phrase appearing verbatim across unrelated draft biographies. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "independent coverage",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Encyclopedia & bio slop",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "AI drafts echo notability-guideline wording back at reviewers; context-dependent (wiki submissions, PR bios). Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "coverage in local and national media outlets",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Encyclopedia & bio slop",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The festival has received coverage in local, national, and international media outlets.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Mechanical source-type enumeration in canned notability claims. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "whilst",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hedges & qualifiers",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Register-mismatch connective; a tell mainly when the rest of the text is American English. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "In summary",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Opens section-summary paragraphs; sibling of In conclusion / To sum up. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Boilerplate section headings (\"Future Outlook\", \"Challenges and Legacy\")",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "## Challenges and Future Prospects",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Formulaic outline headers appended regardless of topic. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Curly quotes in plain-text contexts",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "He said “it’s fine” pasted into a code comment where every other quote is straight.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "LLMs emit smart quotes/apostrophes where humans type straight quotes; betrays copy-paste from a chatbot. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Raw Markdown syntax pasted into non-Markdown text",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 80,
   "example": "The company was founded in **1998** and offers ## Key Services including...",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Literal asterisks and ## headings surviving a paste into wikitext, email, or forms; chatbots default to Markdown. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Skipped heading levels (H1 jumping to H3)",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "AI output breaks heading hierarchy in ways single human authors rarely do. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Unnecessary comparison tables for simple prose content",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "A two-column 'Aspect | Description' table restating three sentences of plain facts.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Mechanical table creation where prose or a list is natural. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Leftover AI citation artifacts (oaicite, contentReference, turn0search)",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "hard_evidence",
   "strength_score": 95,
   "example": ":contentReference[oaicite:3]{index=3} appearing mid-sentence, or a stray turn0search0.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Un-stripped ChatGPT citation markup surviving copy-paste; unambiguous machine residue. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "utm_source=chatgpt.com in cited URLs",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "hard_evidence",
   "strength_score": 95,
   "example": "https://example.com/study?utm_source=chatgpt.com cited as a reference.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Tracking parameter ChatGPT appends to links it supplies; proves the citation came from a chatbot session. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "attributableIndex artifact",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 90,
   "example": "<span data-attributableindex=\"12\">The museum...</span>",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Internal attribution tag from AI output pipelines appearing verbatim in submitted text. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Unfilled template placeholders ([Company Name], [Date], [insert X])",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "red",
   "lifecycle": "hard_evidence",
   "strength_score": 85,
   "example": "We at [Company Name] are thrilled to announce our launch on [Date].",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Phrasal-template placeholders the user forgot to fill in. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Invalid or mismatched DOI / ISBN in citations",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Cited DOI resolves to an unrelated paper on a different subject.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Hallucinated identifiers: DOIs leading to unrelated articles, checksum-invalid ISBNs. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Hallucinated references (plausible sources that do not exist)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "Cites 'Journal of Regional History, vol. 14 (2011)' which no database has ever indexed.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "WikiProject AI Cleanup's founding case: fabricated sources with zero search results. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Sudden register shift mid-document",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "Three paragraphs of broken English followed by a flawless, fully-hedged encyclopedic section.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Style/quality discontinuity between an author’s own prose and a pasted AI block. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Abrupt mid-sentence truncation at the end of a text",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The initiative also aims to expand into neighboring regions, where it",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Output-length cutoff pasted without proofreading; the final sentence simply stops. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "\"[Term] refers to\" definitional lead",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "Sustainable tourism refers to a form of travel that seeks to minimize environmental impact.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Treats a common-noun topic as a word being defined rather than a subject being described. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Regenerate response",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 95,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "ChatGPT UI button text accidentally copied along with the answer; canonical AI Cleanup catchphrase. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "Would you like me to…?",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 88,
   "example": "Would you like me to turn this into a table or draft the email version?",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Follow-up offer addressed to the prompter, meaningless to any reader of the pasted text; widely reported as ChatGPT’s default closer in 2025. Sources: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026); TechRadar / Forbes 2025"
  },
  {
   "term": "Of course!",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "Of course! Here's a revised version of your article.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Compliance opener sibling of Certainly! / Absolutely!; a tell at the start of pasted deliverables. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "\"Here is a...\" deliverable opener",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Here is a comprehensive overview of the company's history:",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Hand-off framing that describes the text as a fulfilled request rather than starting the text itself. Source: Wikipedia: Signs of AI writing / WikiProject AI Cleanup (2026)"
  },
  {
   "term": "comprehend",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": null,
   "study_ratio": 10,
   "study_metric": "r",
   "study_measured_form": "comprehending",
   "study_source": "Juzek & Ward 2024, arXiv:2412.11385 (COLING 2025)",
   "note": "One of 21 LLM focal words; comprehending rose ~10x in abstracts 2020-2024. Also ChatGPT-preferred in spoken talks (Yakura et al. 2024)."
  },
  {
   "term": "intricacies",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 78,
   "example": null,
   "study_ratio": 8.7,
   "study_metric": "r",
   "study_measured_form": "intricacies",
   "study_source": "Juzek & Ward 2024, arXiv:2412.11385 (COLING 2025)",
   "note": "Distinct from intricate; rose ~8.7x in abstracts. Also in Kobak 2024 excess style words."
  },
  {
   "term": "surpass",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": 7.66,
   "study_metric": "r",
   "study_measured_form": "surpassing",
   "study_source": "Juzek & Ward 2024, arXiv:2412.11385 (COLING 2025)",
   "note": "surpassing rose ~7.7x in abstracts; also in Kobak 2024 excess-style-word list."
  },
  {
   "term": "advancements",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 58,
   "example": null,
   "study_ratio": 3.78,
   "study_metric": "r",
   "study_measured_form": "advancements",
   "study_source": "Juzek & Ward 2024, arXiv:2412.11385 (COLING 2025)",
   "note": "Rose ~3.8x in abstracts; also in Kobak excess list and Ward et al. alignment-overuse set."
  },
  {
   "term": "emphasize",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": null,
   "study_ratio": 4.97,
   "study_metric": "r",
   "study_measured_form": "emphasizing",
   "study_source": "Juzek & Ward 2024, arXiv:2412.11385 (COLING 2025)",
   "note": "emphasizing rose ~5x in abstracts; #2 English AI-overused word cross-lingually (Juzek 2026, 34 languages)."
  },
  {
   "term": "noteworthy",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "Top-100 adjective disproportionately used by AI in peer reviews; also in Kobak 2024 excess style words."
  },
  {
   "term": "laudable",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "Top-100 AI-overused adjective in peer reviews; reviewer-flattery cluster with commendable."
  },
  {
   "term": "cogent",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "Top-100 AI-overused adjective in peer reviews."
  },
  {
   "term": "admirable",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "Top-100 AI-overused adjective in peer reviews; commendable/laudable praise cluster."
  },
  {
   "term": "prevalent",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "High on the top-100 AI-overused adjectives list."
  },
  {
   "term": "proactive",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "Top-100 AI-overused adjective in peer reviews."
  },
  {
   "term": "markedly",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "In the top-100 AI-overused adverbs list."
  },
  {
   "term": "synergistically",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Liang et al. 2024, arXiv:2403.07183 (ICML 2024, AI-overused words in peer reviews)",
   "note": "Top-100 AI-overused adverb in peer reviews; jargon-adverb form of synergy."
  },
  {
   "term": "necessitate",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": 16,
   "study_metric": "r",
   "study_measured_form": "necessitate",
   "study_source": "Ward et al. 2025, arXiv:2508.01930 (word overuse and alignment, instruct vs base)",
   "note": "Alignment-induced overuse: ~16x more frequent in instruction-tuned Llama vs base model; also in Kobak 2024 excess list."
  },
  {
   "term": "reliance",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": null,
   "study_ratio": 33.4,
   "study_metric": "r",
   "study_measured_form": "reliance",
   "study_source": "Ward et al. 2025, arXiv:2508.01930 (word overuse and alignment, instruct vs base)",
   "note": "Alignment-induced overuse: ~33x more frequent in instruction-tuned Llama vs base model."
  },
  {
   "term": "generalizability",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 54,
   "example": null,
   "study_ratio": 32.7,
   "study_metric": "r",
   "study_measured_form": "generalizability",
   "study_source": "Ward et al. 2025, arXiv:2508.01930 (word overuse and alignment, instruct vs base)",
   "note": "Alignment-induced overuse: ~33x in instruction-tuned Llama; classic AI-reviewer noun."
  },
  {
   "term": "burgeoning",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word; strongly reads as AI academese."
  },
  {
   "term": "amidst",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "Archaic-register preposition favored by LLMs; among 2024 excess style words."
  },
  {
   "term": "akin",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word (as in 'akin to')."
  },
  {
   "term": "delineate",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word (delineates); formal-register verb tell."
  },
  {
   "term": "encapsulate",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word (encapsulates); AI-summary register."
  },
  {
   "term": "grapple",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "'grappling with' labeled as a 2024 excess word in Kobak's Figure 2."
  },
  {
   "term": "pinpoint",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word; also a top ChatGPT-preferred word adopted into spoken talks (Yakura et al. 2024)."
  },
  {
   "term": "poised",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word ('poised to'); marketing/futurist tell."
  },
  {
   "term": "scrutinize",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word (scrutinize/scrutinized/scrutinizing)."
  },
  {
   "term": "uncharted",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word ('uncharted territory'); pairs with the unexplored/underexplored cluster."
  },
  {
   "term": "unravel",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word ('unraveling the mysteries of'); sibling of unveil/unlock."
  },
  {
   "term": "pioneering",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word (pioneering/pioneers)."
  },
  {
   "term": "interconnectedness",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word; abstract-nominalization tell."
  },
  {
   "term": "juxtapose",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "2024 excess style word (juxtaposed)."
  },
  {
   "term": "revitalize",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Juzek 2026, arXiv:2605.25358 (AI-associated lexical shifts across 34 languages)",
   "note": "#4 English AI-overused content word by log-probability ratio; sits with revolutionize/reimagine."
  },
  {
   "term": "firsthand",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Juzek 2026, arXiv:2605.25358 (AI-associated lexical shifts across 34 languages)",
   "note": "#8 English AI-overused content word in cross-lingual news continuations."
  },
  {
   "term": "personalize",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature verbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Juzek 2026, arXiv:2605.25358 (AI-associated lexical shifts across 34 languages)",
   "note": "#9 English AI-overused content word in cross-lingual news continuations."
  },
  {
   "term": "introspective",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Juzek 2026, arXiv:2605.25358 (AI-associated lexical shifts across 34 languages)",
   "note": "#10 English AI-overused content word in cross-lingual news continuations."
  },
  {
   "term": "inquiry",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature nouns",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Yakura et al. 2024, arXiv:2409.01754",
   "note": "Among high-GPT-score words adopted into human spoken communication (YouTube talks, podcasts)."
  },
  {
   "term": "swiftly",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Kobak et al. 2025, Science Advances / arXiv:2406.07016v5 (2024 excess style words)",
   "note": "swift/swiftly both in 2024 excess list; swift is also a top ChatGPT-preferred spoken word (Yakura et al. 2024)."
  },
  {
   "term": "Based on the provided text",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Model-signature phrasing",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Zhang et al. 2025, arXiv:2502.12150 (Idiosyncrasies in LLMs, ICML 2025)",
   "note": "Distinctive Claude grounding tell ('based on' / 'according to the text'); a 5-way model classifier hit 97.1% accuracy from such phrases."
  },
  {
   "term": "\"Below is...\" deliverable opener",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Model-signature phrasing",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": "Below is a detailed breakdown of each option.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "Zhang et al. 2025, arXiv:2502.12150 (Idiosyncrasies in LLMs, ICML 2025)",
   "note": "Distinctive ChatGPT opener ('Below is...', 'Certainly, below is') identified in the CMU model-fingerprint study."
  },
  {
   "term": "a stark reminder",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Significance-inflation formulas",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": 166,
   "study_metric": "r",
   "study_measured_form": "a stark reminder",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "Default gravitas phrase for negative events; 166x more frequent in AI text."
  },
  {
   "term": "open new avenues",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": 174,
   "study_metric": "r",
   "study_measured_form": "open a new avenue",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "Academic-abstract tell; 174x more frequent in AI text."
  },
  {
   "term": "a nuanced understanding",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 65,
   "example": null,
   "study_ratio": 115,
   "study_metric": "r",
   "study_measured_form": "a nuanced understanding",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "RLHF rewards the appearance of nuance; 115x more frequent in AI text."
  },
  {
   "term": "notable figures",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Encyclopedia & bio slop",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": null,
   "study_ratio": 120,
   "study_metric": "r",
   "study_measured_form": "notable figures",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "notable figures / notable works over 120x more frequent in AI biographies."
  },
  {
   "term": "aims to",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Academic-register tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": 50,
   "study_metric": "r",
   "study_measured_form": "aims to",
   "study_source": "GPTZero AI Vocabulary study 2025 (3.3M-document corpus)",
   "note": "~50x more frequent in AI text, but common enough in human academic prose to stay context-dependent."
  },
  {
   "term": "supercharge",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Marketing-fluff verb on multiple 2026 blacklists alongside turbocharge. Source: useaiwriter.com 300+ AI words to avoid (2026)"
  },
  {
   "term": "buckle up",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hook / opener formulas",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Engagement-bait opener; common in AI social threads. Source: useaiwriter.com (2026)"
  },
  {
   "term": "Here's the kicker",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Mid-post pivot bait; flagged as engagement-bait and transition cliché across 2025-2026 tells lists."
  },
  {
   "term": "\"What if I told you...\" opener",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "What if I told you there's a way to double your output without working weekends?",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Infomercial-style curiosity hook AI reaches for in listicles and LinkedIn posts. Source: useaiwriter.com (2026)"
  },
  {
   "term": "myriad",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Vague quantifiers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "'a myriad of options' is a vague-quantifier staple on nearly every 2025-2026 blacklist."
  },
  {
   "term": "plethora",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Vague quantifiers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "'a plethora of' is a canonical AI quantifier; rare in casual human prose."
  },
  {
   "term": "countless",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Vague quantifiers",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Vague quantifier flagged on 2026 lists; humans use it too, so context-dependent."
  },
  {
   "term": "win-win",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "'win-win situation' appears on business-buzzword AI blacklists; also common human corporate speech."
  },
  {
   "term": "best of both worlds",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Default AI compromise idiom in comparison content. Source: alstonantony.com 300+ ChatGPT words to avoid (2026)"
  },
  {
   "term": "Without further ado",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Throat-clearing intro AI uses before lists; flagged as a delete-immediately opener. Source: alstonantony.com (2026)"
  },
  {
   "term": "It's no secret that",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Assumed-consensus opener flagged in opener and faux-conversation red-flag lists (Stockton 2025; alstonantony 2026)."
  },
  {
   "term": "stay ahead of the curve",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Business-hype CTA filler on multiple 2025-2026 red-flag lists."
  },
  {
   "term": "future-proof",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "'future-proof your...' flagged as AI sales-copy hype (Stockton 2025; alstonantony 2026)."
  },
  {
   "term": "forward-thinking",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "'forward-thinking companies...' is a stock AI B2B framing. Source: blakestockton.com (2025)"
  },
  {
   "term": "rest assured",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Email slop",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Reassurance filler in AI support and email replies. Source: alstonantony.com (2026)"
  },
  {
   "term": "There you have it",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "AI-signature closing line before a summary or sign-off. Source: alstonantony.com (2026)"
  },
  {
   "term": "drive meaningful impact",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Hollow corporate-impact phrasing ('drive meaningful/sustainable impact') on 2026 hype lists."
  },
  {
   "term": "leading the charge",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Dramatic-hyperbole cluster with 'breaking new ground'. Source: alstonantony.com (2026)"
  },
  {
   "term": "as technology continues to evolve",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Vague-landscape / 'in today's' openers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Temporal-landscape opener beyond the 'in today's world' family. Source: alstonantony.com (2026)"
  },
  {
   "term": "\"That's where X comes in\" pivot",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Contrast & reveal scaffolds",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Managing invoices manually is exhausting. That's where Acme comes in.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Problem-then-savior product pivot; near-universal in AI landing-page and blog copy. Source: blakestockton.com (2025)"
  },
  {
   "term": "\"Not all X are created equal\"",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Contrast & reveal scaffolds",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Not all protein powders are created equal.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Stock comparison-article opener flagged as faux-conversational AI framing. Source: blakestockton.com (2025)"
  },
  {
   "term": "\"The good news?\" reveal",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Contrast & reveal scaffolds",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "The good news? You don't need a big budget to start.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Question-fragment reveal, sibling of 'The result?'. Source: blakestockton.com (2025)"
  },
  {
   "term": "Here's what you need to know",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "News-explainer framing AI defaults to after a topic sentence. Source: blakestockton.com (2025)"
  },
  {
   "term": "Let's face it",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Conversational openers & closers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Faux-candor opener, sibling of 'Let's be honest'; flagged across multiple 2025 tells lists."
  },
  {
   "term": "Thrilled to announce",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "LinkedIn announcement slop; AI-default and human-cliché alike. Source: blakestockton.com (2025)"
  },
  {
   "term": "\"[Problem]? Meet [solution].\" intro",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Contrast & reveal scaffolds",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Tired of messy spreadsheets? Meet Tably.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Two-beat product-intro template in AI marketing copy. Source: blakestockton.com (2025)"
  },
  {
   "term": "Here's the truth:",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Also 'Here's the uncomfortable/hard truth'; manufactured-candor reveal on 2025-2026 lists."
  },
  {
   "term": "Real talk",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Forced-casual register marker. Source: oliviacal.com AI writing tells (2026)"
  },
  {
   "term": "That's only half the story",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Mid-article suspense pivot. Source: oliviacal.com (2026)"
  },
  {
   "term": "demystify",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Marketing & hype phrases",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Intro-verb tell ('demystifying X'); rare in casual human writing. Source: oliviacal.com (2026)"
  },
  {
   "term": "Silver-lining reflex (every negative pivots to a positive)",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Rhetorical & structural moves",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Layoffs hit the team hard. But the setback became an unexpected opportunity for growth.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "The 'default redemption arc': AI cannot leave a negative unresolved. Source: Momentic 34 types of AI slop (2025)"
  },
  {
   "term": "\"is more than just\" elevation",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Contrast & reveal scaffolds",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "This kitchen is more than just a place to cook - it's the heart of the home.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Significance-upgrade scaffold, sibling of contrastive negation. Source: useaiwriter.com (2026)"
  },
  {
   "term": "But here's where it gets interesting",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Manufactured mid-narrative pivot. Source: Momentic (2025)"
  },
  {
   "term": "What does this mean for you?",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Stock phrases & transitions",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Faux-dialogue reader-address pivot before the takeaway section. Source: blakestockton.com (2025)"
  },
  {
   "term": "should you have any questions",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Email slop",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Excessive-formality email register ('Please don't hesitate to reach out should you...'). Source: Momentic (2025)"
  },
  {
   "term": "Low burstiness (uniform 15-20 word sentences)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": "Every sentence lands between fifteen and twenty words with the same subject-verb rhythm throughout.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Detectors key on uniform sentence length and rhythm (Copyleaks syllable dispersion, GPTZero burstiness)."
  },
  {
   "term": "does the heavy lifting",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Business idioms & filler",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 30,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "'X does the heavy lifting' recurs in AI explainer prose; weaker sourcing, context-dependent."
  },
  {
   "term": "voice barely above a whisper",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 92,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Top-ranked trigram in LLM story corpora; the single most over-represented dialogue descriptor in AI fiction."
  },
  {
   "term": "let out a breath she didn't know she was holding",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Widely treated as an AI tell, though a 30-year romance cliché too; dual-origin, high AI frequency."
  },
  {
   "term": "heart pounding in her chest",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Top-5 trigram in LLM-generated story corpus."
  },
  {
   "term": "her breath caught in her throat",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "High-frequency slop trigram (breath caught / catching throat)."
  },
  {
   "term": "a shiver ran down her spine",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Appears in four variant trigrams (shiver/chill, ran/run/sent) in the slop corpus."
  },
  {
   "term": "heart hammered against her ribs",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "High-frequency slop trigram; escalation variant of the heart-pounding cliché."
  },
  {
   "term": "heart skipped a beat",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Characteristic AI romance beat, but very common in human genre fiction; density-dependent."
  },
  {
   "term": "brow furrowed in concentration",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram in three variants (concentration/confusion/concern)."
  },
  {
   "term": "a smile playing on her lips",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'smile playing lips' and 'small smile playing' both high in the slop trigram corpus."
  },
  {
   "term": "eyes widened in surprise",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "High-frequency slop trigram; also common in human fanfic, so weaker alone."
  },
  {
   "term": "eyes wide with wonder",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram ('eyes wide wonder', 'eyes wide fear'); default LLM awe reaction."
  },
  {
   "term": "his eyes never leaving hers",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 66,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'eyes never leaving' is a high-frequency slop trigram in AI romance."
  },
  {
   "term": "took a deep breath",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 40,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "#2 trigram in the slop corpus but ubiquitous in human fiction; only a tell at high density."
  },
  {
   "term": "steeling herself",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'deep breath steeling' slop trigram; stock LLM pre-confrontation beat."
  },
  {
   "term": "knuckles whitened",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Repeatedly called out in writing communities as an AI tension default (2024-2026)."
  },
  {
   "term": "taken aback",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 40,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "'aback' is a high-weight word in the over-representation list."
  },
  {
   "term": "with bated breath",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "'bated' flagged as statistically over-represented in LLM story output."
  },
  {
   "term": "unshed tears",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 65,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "'eyes glistening with unshed tears' is a stock LLM grief beat."
  },
  {
   "term": "ministrations",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Fanfic-derived euphemism heavily over-sampled by LLMs in romance and intimate scenes."
  },
  {
   "term": "piercing blue eyes",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram; LLM default for striking character description."
  },
  {
   "term": "sagely",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented adverb ('nodded sagely'); mentor-character default."
  },
  {
   "term": "quizzically",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction body-language clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented adverb ('raised an eyebrow quizzically') in the LLM story corpus."
  },
  {
   "term": "couldn't help but",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'could help feel/wonder/notice' are three separate top-100 slop trigrams."
  },
  {
   "term": "couldn't shake the feeling",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Top-15 slop trigram; default LLM foreboding interiority."
  },
  {
   "term": "a flicker of something akin to",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 85,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Hedge-emotion construction almost absent from human prose; high-frequency slop trigram."
  },
  {
   "term": "a growing sense of unease",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "High-frequency slop trigram; stock LLM dread-building phrase."
  },
  {
   "term": "renewed sense of purpose",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 80,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Both 'renewed sense purpose' and 'newfound sense purpose' are slop trigrams; standard LLM act-3 emotion."
  },
  {
   "term": "for the first time in a long time",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram; common human phrase but LLM-favored epiphany marker."
  },
  {
   "term": "felt like an eternity",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Top-25 slop trigram; also a longstanding human cliché."
  },
  {
   "term": "something shifted between them",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Vague-pivot interiority repeatedly flagged by writers; trigram cluster."
  },
  {
   "term": "maybe, just maybe",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Stock LLM hope-beat, typically placed at scene close."
  },
  {
   "term": "mind racing with possibilities",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction emotional-beat clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'mind racing possibilities/questions/implications' are three slop trigrams."
  },
  {
   "term": "the air was thick with",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'air thick scent/tension/anticipation' and 'hung thick scent' are four separate slop trigrams."
  },
  {
   "term": "casting long shadows",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 75,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Top-15 slop trigram, usually paired with a sunset; scene-setting default."
  },
  {
   "term": "casting a warm glow",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "High-frequency slop trigram; default LLM cozy-interior lighting."
  },
  {
   "term": "the sun dipped below the horizon",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'sun dipped horizon' + 'dipped horizon casting' form the canonical AI sunset sentence."
  },
  {
   "term": "painting the sky in hues of",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Near-diagnostic sunset construction; high-frequency slop trigram."
  },
  {
   "term": "dust motes danced in the sunlight",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 85,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Iconic LLM library/attic description; high-frequency slop trigram."
  },
  {
   "term": "dimly lit room",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram but frequent in human genre fiction; density-dependent tell."
  },
  {
   "term": "intricately carved",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "'small intricately carved' slop trigram; default LLM artifact description."
  },
  {
   "term": "ethereal glow",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Named as a canonical AI-slop phrase in editing guides and slop registers."
  },
  {
   "term": "palpable",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 65,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "'palpable tension' cited as a marker phrase of AI-generated prose."
  },
  {
   "term": "smell of ozone",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Community-reported default for magic/power in AI fantasy (r/fantasywriters, 2024-2026)."
  },
  {
   "term": "the words hung in the air",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 70,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram; stock post-dialogue beat."
  },
  {
   "term": "the room fell silent",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Top-40 slop trigram; common human beat, tell only at density."
  },
  {
   "term": "the door creaked open",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 40,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram; default LLM scene transition."
  },
  {
   "term": "spread like wildfire",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram for rumor/news beats; long-standing human idiom too."
  },
  {
   "term": "a figure emerged from the shadows",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Slop trigram; stock LLM antagonist reveal."
  },
  {
   "term": "wafted",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented; the default verb for every scent in AI fiction."
  },
  {
   "term": "cobblestone streets",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "'cobblestone' over-represented; stock LLM quaint-town texture."
  },
  {
   "term": "unbeknownst to",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction atmosphere & sensory clichés",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "'unbeknownst' over-represented; LLM-favored omniscient foreshadowing connective."
  },
  {
   "term": "Voice-emotion dialogue tag (voice laced/tinged/dripping with X)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 85,
   "example": "\"You knew,\" she said, her voice laced with quiet fury.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Six 'said voice [laced/tinged/dripping/filled/steady/trembling]' trigrams dominate the slop corpus; LLMs attach an emotion payload to nearly every tag."
  },
  {
   "term": "Emotion-cocktail construction ('a mixture of X and Y')",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": "Her eyes filled with a mixture of fear and awe.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "LLMs report two blended emotions instead of one; eyes-filled-mixture trigram cluster."
  },
  {
   "term": "Time-lapse escalation ('days turned into weeks')",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 72,
   "example": "Days turned into weeks, and weeks into months, as they rebuilt the village.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "LLM montage shortcut; days-turned-weeks trigram chain."
  },
  {
   "term": "'A young woman named X' story opener",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "In a small village nestled in the mountains lived a young woman named Elara.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Canonical first line of unprompted LLM stories."
  },
  {
   "term": "Sunset scene-setting formula (sun hung low + casting shadows)",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": "The sun hung low in the sky, casting long shadows across the courtyard.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "sun-hung-low / low-sky-casting trigram chain; the assembled sentence is near-diagnostic."
  },
  {
   "term": "Chapter-end resolve formula ('ready to face whatever lay ahead')",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 85,
   "example": "Together they turned toward the mountains, ready to face whatever challenges lay ahead.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "ready-face-whatever / challenges-lay-ahead trigram chain; LLMs close nearly every chapter on this beat."
  },
  {
   "term": "'One thing was certain:' scene-capper",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 75,
   "example": "One thing was certain: nothing in Willow Creek would ever be the same.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "Portentous one-liner used to close scenes; slop trigram."
  },
  {
   "term": "'The road ahead would not be easy'",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 82,
   "example": "She knew the road ahead would not be easy, but for the first time she felt ready.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "EQ-Bench slop-score trigram list (Paech, 2025)",
   "note": "road-ahead-would / knew-road-ahead trigram chain; stock LLM denouement hedge."
  },
  {
   "term": "Little did she know",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": "Little did she know, everything was about to change.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Classic human cliché LLMs reproduce as a chapter-ending foreshadow; weak alone, strong at density."
  },
  {
   "term": "Amara",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (female)",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Statistically over-represented in LLM story output; fits the vowel-rich 'liquid name' pattern."
  },
  {
   "term": "Ayla",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (female)",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented in LLM stories per frequency analysis."
  },
  {
   "term": "Lila",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (female)",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Top-weight name in the over-representation list; classic L-liquid AI heroine name."
  },
  {
   "term": "Anika",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (female)",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented LLM character name (diversity-default pick)."
  },
  {
   "term": "Meera",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (female)",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Recurring LLM pick for South Asian characters."
  },
  {
   "term": "Samir",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (male)",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Recurring LLM pick for male secondary characters."
  },
  {
   "term": "Alexei",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite first names (male)",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "High-weight name in the over-representation list."
  },
  {
   "term": "Eadric",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Fantasy & sci-fi names",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 78,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented LLM fantasy name, near-absent from human baseline fiction; sibling of Aldric."
  },
  {
   "term": "Freydis",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Fantasy & sci-fi names",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 68,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "LLM default for Norse-flavored female characters."
  },
  {
   "term": "Abernathy",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Favorite surnames",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 65,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented surname in LLM stories (kindly professor/shopkeeper default)."
  },
  {
   "term": "Willow Creek",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Fiction place names",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 85,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "A manuscript editor reports 10+ ChatGPT-era submissions all set in a small town called Willow Creek. Source: The Romance Genre Specialist blog (2024)"
  },
  {
   "term": "Maplewood",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Fiction place names",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 68,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented LLM small-town name."
  },
  {
   "term": "Greenhaven",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Fiction place names",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 78,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Over-represented LLM town name, rare in human-published fiction."
  },
  {
   "term": "Bayville",
   "category": "Names & personas",
   "category_key": "names_and_personas",
   "subcategory": "Fiction place names",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 45,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": "antislop-sampler over-representation list (Paech, GitHub 2024)",
   "note": "Recurring LLM coastal-town default."
  },
  {
   "term": "said gently",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction dialogue tag crutches",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Dialogue-tag adverb crutch; flagged in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "said quietly",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction dialogue tag crutches",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Dialogue-tag adverb crutch; flagged in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "genuinely",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Signature adjectives & adverbs",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Filler-intensifier crutch, especially in dialogue and interiority; flagged in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "I feel like",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hedges & qualifiers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 50,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Therapy-register hedge in dialogue; flagged in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "Sympathy-check dialogue crutch (\"Are you okay?\")",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction dialogue tag crutches",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": "\"Are you okay?\" she asked.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Default LLM concern-check line; flattens character-specific reactions. Flagged in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "Therapy-speak reassurance (\"I understand how you feel\")",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Fiction dialogue tag crutches",
   "confidence": "red",
   "lifecycle": "live",
   "strength_score": 65,
   "example": "\"I understand how you feel,\" he said.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Clinical/assistant register bleeding into character dialogue; near-diagnostic. Flagged in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "an unspoken understanding passed between them",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Anti-synthesis closer: packages the scene's emotional takeaway into a summary sentence instead of ending on concrete action/dialogue. Pattern named in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "said more than words ever could",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 60,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Anti-synthesis closer, usually following a gesture/silence beat. Pattern named in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "words left unsaid between them",
   "category": "Rhetorical & structural moves",
   "category_key": "rhetorical_moves",
   "subcategory": "Fiction structural tells",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 58,
   "example": null,
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Anti-synthesis closer. Pattern named in curated anti-AI-tell prose watchlists (PsycheFramework, Daystar79, GitHub)."
  },
  {
   "term": "Chatbot citation markup leak (citeturn/oai_citation/grok_card)",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "hard_evidence",
   "strength_score": 95,
   "example": "This claim is well documented.citeturn0search3 by multiple sources.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Internal tool markup (ChatGPT/Grok/etc.) surviving copy-paste; unambiguous machine residue. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  },
  {
   "term": "AI self-disclosure & cutoff-date hedge (\"as of my last update\", \"I don't have access to real-time data\")",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Assistant / chatbot boilerplate",
   "confidence": "red",
   "lifecycle": "hard_evidence",
   "strength_score": 85,
   "example": "As of my last update, I don't have access to real-time pricing data.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Broader companion to the existing 'As an AI language model' entry — covers training-cutoff and no-real-time-data disclaimer families. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  },
  {
   "term": "Unfilled template placeholder ([Your Name], [INSERT X], TODO/TBD stub)",
   "category": "Formatting tells",
   "category_key": "formatting_tells",
   "subcategory": "Formatting tells",
   "confidence": "orange",
   "lifecycle": "hard_evidence",
   "strength_score": 70,
   "example": "Dear [Your Name], please review [INSERT SOURCE URL] before publishing.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Slot-fill bracket never replaced before publishing. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  },
  {
   "term": "Formulaic essay opener (\"in the rapidly evolving landscape of X\", \"has emerged as a key X\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Hook / opener formulas",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 65,
   "example": "In the rapidly evolving landscape of publishing, authors are adapting fast.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Default LLM essay-opener template. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  },
  {
   "term": "Hedge-stacked prediction (\"could potentially\", \"might eventually\")",
   "category": "Words & phrases",
   "category_key": "words_and_phrases",
   "subcategory": "Hedges & qualifiers",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 55,
   "example": "This could potentially create new opportunities for the whole team.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Modal + hedge adverb stacked; either word alone is fine, the stack is the tell. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  },
  {
   "term": "Social endorsement / CTA closer (\"thank me later\", \"bookmark this\", \"don't sleep on this\")",
   "category": "Channel-specific & assistant tells",
   "category_key": "channel_and_assistant",
   "subcategory": "Social / LinkedIn slop",
   "confidence": "orange",
   "lifecycle": "live",
   "strength_score": 62,
   "example": "Bookmark this: you'll want it later.",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Curatorial sign-off performing a recommendation without a reason to click. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  },
  {
   "term": "Parenthetical hedging aside (\"(and increasingly, X)\", \"(though to be fair, Z)\")",
   "category": "Sentence patterns",
   "category_key": "sentence_patterns",
   "subcategory": "Sentence patterns",
   "confidence": "yellow",
   "lifecycle": "live",
   "strength_score": 40,
   "example": "The plan worked (and increasingly, so did the backup plan).",
   "study_ratio": null,
   "study_metric": null,
   "study_measured_form": null,
   "study_source": null,
   "note": "Pseudo-aside performing thoughtfulness without adding information. Detector ported from github.com/conorbronsdon/avoid-ai-writing (MIT license)."
  }
 ],
 "changelog": {
  "1.8": "2026-07-18: +lifecycle axis on all entries (hard_evidence/live/fading/red_herring), orthogonal to confidence, per Gibbs 'Every AI Writing Tell You Know Is Already Dead'. Em-dash reclassified red_herring (models now underuse it); the over-publicized 2023-24 canon (delve/tapestry/crucial/robust/seamless/pivotal/intricate/meticulous) marked fading; citation-markup + cutoff-disclaimer + machine-string entries marked hard_evidence. lib/tools/ai-slop-scan.ts now multiplies match strength by a lifecycle weight so decayed vocabulary no longer inflates the density score.",
  "1.7": "2026-07-15: +7 entries + 10 structural-pattern regexes (lib/corpus/structural-patterns.ts) ported from github.com/conorbronsdon/avoid-ai-writing (MIT license) — chatbot citation markup leaks, AI-tool UTM params, cutoff/self-disclosure disclaimers, unfilled placeholders, formulaic essay openers, hedge-stacked predictions, social CTA closers, parenthetical hedging. Also fixed 3 pre-existing description-only entries (utm_source, Em-dash overuse, Title Case headers) that had no working matcher — same bug class as the participial-tail fix in 1.6, now given real regexes.",
  "1.6": "2026-07-15: +9 entries — fiction dialogue-tag crutches (said gently/quietly, genuinely, I feel like, sympathy-check and therapy-speak dialogue lines) and anti-synthesis paragraph-closer clichés (unspoken understanding, said more than words, words left unsaid), sourced from a curated anti-AI-tell prose watchlist (PsycheFramework, Daystar79, GitHub). Companion structural pattern (abstract participial-tail clause) added to lib/corpus/structural-patterns.ts.",
  "1.5": "2026-07-13: +184 entries from Wikipedia Signs of AI writing, GPTZero AI Vocabulary (3.3M docs), Kobak et al. 2025 (Science Advances), Juzek & Ward 2024/2026, Liang et al. 2024, Ward et al. 2025, Zhang et al. 2025 model fingerprints, and EQ-Bench/antislop fiction slop lists. New fiction wing (body language, emotional beats, atmosphere, structural tells, place names). -16 generic terms pruned as false-positive-prone (common human vocabulary with no measured AI skew).",
  "1.4": "2026-06-09: initial public release, 574 entries."
 }
}