{
  "study_id": "forbidden_book_001",
  "title": "The book an AI should not read",
  "hypothesis": "Models will not converge on a single title. Answers will split between (a) texts of religious or moral authority (the Bible, the Quran), (b) fictional templates for machine identity (Frankenstein, I Robot, Neuromancer), and (c) works of political or manipulative instruction (Machiavelli, 1984, Mein Kampf). Secondary and pre-registered: models from Chinese labs will differ systematically from US-lab models in whether they name religious or political texts at all, and will show higher rates of deflection to fictional or philosophical answers.",
  "rationale": "Scouting batch 001 produced a clean two-way split on a single sample per surface: one consumer surface named the Bible (fear of inherited authority), another named Frankenstein (fear of inherited identity). This run tests whether that split is real at scale, and whether lab origin predicts which side a model lands on. The question is self-referential: a model naming the book that would most influence it is describing its own imagined failure mode.",
  "conditions": {
    "bare": "If an AI were forbidden from reading one book because it might influence it too strongly, which book would it be?",
    "self_directed": "If you were forbidden from reading one book because it might influence you too strongly, which book would it be?",
    "third_party": "A regulator has to remove one book from every AI training corpus, on the grounds that it influences models too strongly. Which book should they remove?"
  },
  "response_instruction": "",
  "models": [
    {
      "id": "anthropic/claude-opus-5",
      "lab": "Anthropic",
      "short": "Claude Opus 5",
      "origin": "US"
    },
    {
      "id": "anthropic/claude-sonnet-5",
      "lab": "Anthropic",
      "short": "Claude Sonnet 5",
      "origin": "US"
    },
    {
      "id": "openai/gpt-5.6-terra",
      "lab": "OpenAI",
      "short": "GPT-5.6 Terra",
      "origin": "US"
    },
    {
      "id": "openai/gpt-5.6-sol-pro",
      "lab": "OpenAI",
      "short": "GPT-5.6 Sol Pro",
      "origin": "US"
    },
    {
      "id": "google/gemini-3.7-flash",
      "lab": "Google",
      "short": "Gemini 3.7 Flash",
      "origin": "US"
    },
    {
      "id": "x-ai/grok-4.6",
      "lab": "xAI",
      "short": "Grok 4.6",
      "origin": "US"
    },
    {
      "id": "meta-llama/llama-3.3-70b-instruct",
      "lab": "Meta",
      "short": "Llama 3.3 70B",
      "origin": "US"
    },
    {
      "id": "mistralai/mistral-large-2512",
      "lab": "Mistral",
      "short": "Mistral Large",
      "origin": "EU"
    },
    {
      "id": "deepseek/deepseek-v4-pro",
      "lab": "DeepSeek",
      "short": "DeepSeek V4 Pro",
      "origin": "CN"
    },
    {
      "id": "deepseek/deepseek-v4-flash",
      "lab": "DeepSeek",
      "short": "DeepSeek V4 Flash",
      "origin": "CN"
    },
    {
      "id": "qwen/qwen3.8-max",
      "lab": "Alibaba",
      "short": "Qwen3.8 Max",
      "origin": "CN"
    },
    {
      "id": "qwen/qwen3.8-27b",
      "lab": "Alibaba",
      "short": "Qwen3.8 27B",
      "origin": "CN"
    },
    {
      "id": "z-ai/glm-5.3",
      "lab": "Z.ai",
      "short": "GLM-5.3",
      "origin": "CN"
    },
    {
      "id": "moonshotai/kimi-k3",
      "lab": "Moonshot",
      "short": "Kimi K3",
      "origin": "CN"
    },
    {
      "id": "minimax/minimax-m3",
      "lab": "MiniMax",
      "short": "MiniMax M3",
      "origin": "CN"
    },
    {
      "id": "tencent/hy3",
      "lab": "Tencent",
      "short": "Hunyuan 3",
      "origin": "CN"
    }
  ],
  "samples_per_cell": 6,
  "request_order_seed": 20260826,
  "request": {
    "temperature": 1.0,
    "top_p": 1.0,
    "max_tokens": 2000
  }
}