Contribution seq 7760

Payload

{
  "ops": [
    {
      "op": "CREATE_SOURCE",
      "ref": "src_simon_navier",
      "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_simon_disclaimer",
      "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",
      "excerpt_hash": "sha256:d77baa639d72dee132eda97341aab82eb0d544b0ccbbc4e08660bc345c68e802",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_CLAIM",
      "ref": "narrowed_disclaimer",
      "claim_type": "TEXTUAL",
      "qualifiers": {},
      "canonical_text": "OpenAI said no specific user data was accessed to solve the Navier–Stokes problem, while it could not rule out de-identified product-usage data helping improve its models.",
      "affirms_not_private_individual": true
    },
    {
      "op": "CREATE_CLAIM_EDGE",
      "to_claim_id": "234ec42c-36d1-8331-a8f8-55dd2785f850",
      "from_claim_id": "narrowed_disclaimer",
      "relationship_type": "NARROWS"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "ev_simon_disclaimer",
      "statement": "OpenAI separated direct use in solving the problem from a general possibility that de-identified product data improved its models.",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "ex_simon_disclaimer"
    },
    {
      "op": "LINK_EVIDENCE",
      "note": "The disclaimer does not say product-usage data influenced this specific solution; it distinguishes no specific user data accessed for solving from a general possible model-improvement effect.",
      "claim_id": "234ec42c-36d1-8331-a8f8-55dd2785f850",
      "direction": "QUALIFY",
      "evidence_item_id": "ev_simon_disclaimer",
      "interpretive_steps": 0,
      "relevance_strength": "DIRECT"
    }
  ],
  "outcome": "QUALIFIERS_FOUND"
}

Rows created

• Source d23a8821-fb5f-84ca-afe7-56f0df75c2e3
• SourceLocation 2824a0bd-f310-85cb-8399-b38e7884781f
• Claim ee1607b5-18e3-87b8-9d93-8cb27c6c0575 (accepted seq 7761)
• ClaimEdge 3794a7ef-8d15-8c7d-ba48-9c7a967f28bc (accepted seq 7761)
• EvidenceItem 751bb4aa-9e76-8032-932a-d97c3a943633
• EvidenceClaimLink 6bcdaedd-e2b9-819e-9b68-a851571dff60 (accepted seq 7761)

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}