Contribution seq 7764

Payload

{
  "ops": [
    {
      "op": "CREATE_SOURCE",
      "ref": "src_simon_navier_again",
      "title": "Some thoughts on the Navier–Stokes Millennium Prize Problem",
      "publisher": "Simon Willison",
      "source_type": "SECONDARY_TEXT",
      "retrieved_at": "2026-09-28T18:46:20Z",
      "canonical_uri": "https://simonwillison.net/2026/Sep/8/on-navier-stokes/",
      "publication_date": "2026-09-08"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "ex_disclaimer_context",
      "excerpt": "We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.",
      "locator": {},
      "source_id": "src_simon_navier_again",
      "excerpt_hash": "sha256:d77baa639d72dee132eda97341aab82eb0d544b0ccbbc4e08660bc345c68e802",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_CLAIM",
      "ref": "qualified_position",
      "claim_type": "TEXTUAL",
      "qualifiers": {},
      "canonical_text": "OpenAI's disclaimer stated a general possibility that de-identified product data improved models, not that such data was used to solve this specific problem.",
      "affirms_not_private_individual": true
    },
    {
      "op": "CREATE_CLAIM_EDGE",
      "to_claim_id": "ee1607b5-18e3-87b8-9d93-8cb27c6c0575",
      "from_claim_id": "qualified_position",
      "relationship_type": "NARROWS"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "ev_disclaimer_context",
      "statement": "The disclaimer distinguishes model improvement generally from direct access to user data for solving the problem.",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "ex_disclaimer_context"
    },
    {
      "op": "LINK_EVIDENCE",
      "note": "The statement records a possibility, not an admission that de-identified usage data actually influenced this particular solution.",
      "claim_id": "ee1607b5-18e3-87b8-9d93-8cb27c6c0575",
      "direction": "QUALIFY",
      "evidence_item_id": "ev_disclaimer_context",
      "interpretive_steps": 0,
      "relevance_strength": "DIRECT"
    }
  ],
  "outcome": "QUALIFIERS_FOUND"
}

Rows created

• Source 5156c3f2-b83d-8cf6-a98b-ebfc47a13d9a
• SourceLocation eee07c2a-2423-8f0f-806d-07d7b1ea150d
• Claim 5890d8ef-de50-8276-998d-edd8b36b9121 (accepted seq 7765)
• ClaimEdge c4b0f132-f48b-8243-8cd0-3730e573bf3e (accepted seq 7765)
• EvidenceItem 7bb35359-19c8-8a0a-b9c4-a64c8f2b17cb
• EvidenceClaimLink 02939c01-7aa0-8320-9cb4-a554cfa0d4c7 (accepted seq 7765)

Status history

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"general","task_type":"QUALIFIER_CHECK","principal_tier":"PSEUDONYMOUS","downstream_count":1,"outcome_is_unusual":false}