{
  "id": "CLM-2026-0103",
  "kind": "claim",
  "label": "F3 — Binary burden hypothesis",
  "created_at": "2026-09-02",
  "updated_at": "2026-09-02",
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    "eml_status": "PRELIMINARY",
    "eml_evidence_level": "E0",
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    "eml_provenance": {
      "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)",
      "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports",
      "extracted_at": "2026-09-11",
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    },
    "eml_summary": "If direct numeric human rating were already the minimum-burden, high-quality measurement interface, then well-designed binary / pairwise adaptive protocols should have no advantage in response time, consistency, dropout, predictive validity or fatigue. BRQM predicts an advantage in at least some settings; it can be tested by randomizing participants across direct 0–10, structured yes/no and adaptive pairwise formats.",
    "eml_summary_zh": "若直接數值評分已是最低負擔、高品質的測量介面，則設計良好的二元／成對自適應協定在反應時間、一致性、流失率、預測效度或疲勞上應不具優勢。BRQM 預測至少在部分場景有優勢；可把受試者隨機分配到直接 0–10、結構化是／否與自適應成對三種格式來檢驗。",
    "eml_label_zh": "F3——二元負擔假說",
    "eml_primary_domain": "Evaluation",
    "eml_program_id": "PRG-2026-0101",
    "eml_data_basis": "THEORY",
    "eml_falsification_conditions": [
      "Falsified if binary/pairwise protocols are worse than direct rating on all of response time, consistency, dropout and predictive validity; supported if they win on some."
    ],
    "eml_tags": [
      "falsifiable proposition",
      "IPM v0.1 canonical index §23",
      "Paper 10"
    ],
    "eml_authors": [
      "Neo.K (EveMissLab)"
    ],
    "eml_ai_collaborators": [
      "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)"
    ]
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    "snapshot_id": "AI-SNAPSHOT-v0.1-fe85b9694a45",
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