Step 14: tool results

search_similar_claims

{
  "limit": 6,
  "query": "AI benchmarks overestimate real-world capability; benchmark acceleration reflects overfitting"
}

{
  "query": "AI benchmarks overestimate real-world capability; benchmark acceleration reflects overfitting",
  "results": [
    {
      "id": "2fba320c-eb0d-4c17-85fe-84047a63b83c",
      "kind": "claim",
      "text": "AI benchmarks overestimate models' capabilities on real-world tasks.",
      "claim_type": "evaluative",
      "state": "active",
      "similarity_score": 0.8535572884623351,
      "importance": 0.6,
      "assessment_status": "supported",
      "assessment_confidence": 0.7
    },
    {
      "id": "3675680d-92c0-4815-bf07-33f659720bea",
      "kind": "claim",
      "text": "Reliance on AI capability benchmarks leads to systematic overestimation of AI's real-world impact.",
      "claim_type": "causal",
      "state": "active",
      "similarity_score": 0.6855224691367399,
      "importance": 0.6,
      "assessment_status": "supported",
      "assessment_confidence": 0.55
    },
    {
      "id": "0162e66a-d087-4640-95ae-a17539a8f031",
      "kind": "claim",
      "text": "AI capability benchmarks underestimate models' capabilities by limiting elicitation, scaffolding, and iterative feedback.",
      "claim_type": "empirical_derived",
      "state": "active",
      "similarity_score": 0.6567407379336514,
      "importance": 0.4,
      "assessment_status": "supported",
      "assessment_confidence": 0.6
    },
    {
      "id": "ecb10d1f-b391-4e54-b645-8133ad3827ae",
      "kind": "claim",
      "text": "Recent acceleration measured on well-specified AI benchmarks will not generalize to AI research and development.",
      "claim_type": "empirical_derived",
      "state": "active",
      "similarity_score": 0.6124798013267226,
      "importance": 0.6,
      "assessment_status": null,
      "assessment_confidence": null
    },
    {
      "id": "54d65b14-dd70-44f7-9b3b-a9719157f3ad",
      "kind": "claim",
      "text": "Frontier AI benchmark scores can change with inference budgets, scaffolding, or judging protocols while model weights remain fixed.",
      "claim_type": "causal",
      "state": "active",
      "similarity_score": 0.5785437428700237,
      "importance": 0.45,
      "assessment_status": null,
      "assessment_confidence": null
    },
    {
      "id": "945ca910-9669-4585-81d5-0dfa2d93d82c",
      "kind": "claim",
      "text": "AI systems saturated the CORE-Bench research-reproduction benchmark within about fifteen months of scoring roughly 20% in 2024.",
      "claim_type": "empirical_verifiable",
      "state": "active",
      "similarity_score": 0.5657308405726641,
      "importance": 0.3,
      "assessment_status": null,
      "assessment_confidence": null
    }
  ],
  "count": 6
}