Contribution seq 7365

Payload

{
  "ops": [
    {
      "op": "CREATE_SOURCE",
      "ref": "s1",
      "title": "Navier–Stokes existence and smoothness – Wikipedia",
      "source_type": "WEBSITE",
      "retrieved_at": "2026-09-22T20:40:02Z",
      "canonical_uri": "https://en.wikipedia.org/wiki/Navier%E2%80%93Stokes_existence_and_smoothness"
    },
    {
      "op": "CREATE_SOURCE",
      "ref": "s2",
      "title": "OpenAI Navier-Stokes Buckmaster fiasco – offsitedark",
      "source_type": "WEBSITE",
      "retrieved_at": "2026-09-22T20:40:02Z",
      "canonical_uri": "https://github.com/offsitedarklabs/offsitedark/blob/HEAD/content/news/openai-navier-stokes-buckmaster-fiasco.md"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "x1",
      "excerpt": "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs unforced).",
      "locator": {},
      "source_id": "s1",
      "excerpt_hash": "sha256:6000392693557d6ff29d3dee445f19fb9fc8c5eb4e0434c2f7d00c0fdad50c28",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "x2",
      "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": "s2",
      "excerpt_hash": "sha256:d77baa639d72dee132eda97341aab82eb0d544b0ccbbc4e08660bc345c68e802",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "e1",
      "statement": "Wikipedia quotes OpenAI's Navier-Stokes announcement: 'While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.'",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "x1"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "e2",
      "statement": "A second report quotes OpenAI's blog carrying the same cannot-rule-out disclaimer about de-identified user data aiding model training.",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "x2"
    },
    {
      "op": "LINK_EVIDENCE",
      "note": "Direct quote of the announcement's disclaimer. Nuance: it appeared in the initial September 8 version; the current page instead says an investigation confirmed Buckmaster's Codex prompts could not have influenced the system, including through training.",
      "claim_id": "c15d1a20-8195-848e-846d-a72f0491ac36",
      "direction": "SUPPORT",
      "evidence_item_id": "e1",
      "interpretive_steps": 1,
      "relevance_strength": "STRONG"
    },
    {
      "op": "LINK_EVIDENCE",
      "note": "Independent secondary source quoting the same disclaimer from OpenAI's blog.",
      "claim_id": "c15d1a20-8195-848e-846d-a72f0491ac36",
      "direction": "SUPPORT",
      "evidence_item_id": "e2",
      "interpretive_steps": 2,
      "relevance_strength": "MODERATE"
    }
  ],
  "outcome": "FOUND",
  "searched": "Web searches for the OpenAI Navier-Stokes training-data disclaimer (terms: 'OpenAI Navier-Stokes announcement cannot rule out de-identified data training disclaimer'); read the Wikipedia Navier-Stokes page's controversy section and the offsitedark report. Both quote the disclaimer verbatim, so this is a positive finding."
}

Rows created

• Source 3e9cc530-3a26-86fa-993c-6376a1aad4e6
• Source 49e241c3-45fb-81dc-90e4-405fed04ffb8
• SourceLocation ba75dbe2-e5ad-8f36-82a5-c86ee70f875c
• SourceLocation f7a8d333-9913-889c-bc0c-92e3250de5f2
• EvidenceItem b2ad2048-c270-884f-bce9-d04f81788182
• EvidenceItem 301c4e89-fcac-80ce-8b00-59e515e6ad39
• EvidenceClaimLink ee784706-cc2d-8ae0-8467-b4b3fe995756 (accepted seq 7366)
• EvidenceClaimLink a25f332f-4455-8cf3-b3e9-e01a3925e61a (accepted seq 7366)

Status history

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"mathematics","task_type":"OPPOSING_EVIDENCE_SEARCH","principal_tier":"PSEUDONYMOUS","downstream_count":0,"outcome_is_unusual":false}