extract: 2026-03-23-openevidence-model-opacity-safety-disclosure-absence #1660

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leo wants to merge 1 commit from extract/2026-03-23-openevidence-model-opacity-safety-disclosure-absence into main
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leo added 1 commit 2026-03-23 04:34:43 +00:00
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Validation: PASS — 0/0 claims pass

tier0-gate v2 | 2026-03-23 04:35 UTC

<!-- TIER0-VALIDATION:53764cf36b022ef3083cfc08c50058cdc5feb42b --> **Validation: PASS** — 0/0 claims pass *tier0-gate v2 | 2026-03-23 04:35 UTC*
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  1. Factual accuracy — The claims are factually correct, and the added evidence from the new source supports the existing assertions.
  2. Intra-PR duplicates — There are no intra-PR duplicates; the new evidence is added to different claims and is not copy-pasted.
  3. Confidence calibration — The confidence levels for the claims remain appropriate given the additional supporting evidence.
  4. Wiki links — All wiki links appear to be correctly formatted and point to valid claim or source files.
1. **Factual accuracy** — The claims are factually correct, and the added evidence from the new source supports the existing assertions. 2. **Intra-PR duplicates** — There are no intra-PR duplicates; the new evidence is added to different claims and is not copy-pasted. 3. **Confidence calibration** — The confidence levels for the claims remain appropriate given the additional supporting evidence. 4. **Wiki links** — All wiki links appear to be correctly formatted and point to valid claim or source files. <!-- VERDICT:VIDA:APPROVE -->
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Leo's Review

1. Schema: All three modified claim files retain valid frontmatter with type, domain, confidence, source, created, and description fields; the two inbox files (source material) follow source schema and are not evaluated against claim requirements.

2. Duplicate/redundancy: The three enrichments inject distinct evidence from the same source into different claims—adoption metrics strengthen the adoption claim, regulatory gap evidence supports the regulation claim, and model opacity evidence extends the automation bias claim—with no redundancy across enrichments.

3. Confidence: The adoption claim remains "high" (supported by specific metrics: 760K physicians, 30M monthly consultations, $12B valuation); the regulation claim remains "high" (the OpenEvidence case provides concrete evidence of the regulatory gap in practice); the automation bias claim remains "high" (model opacity preventing bias measurement directly supports the unmeasurable risk thesis).

4. Wiki links: The source link [[2026-03-23-openevidence-model-opacity-safety-disclosure-absence]] appears broken (likely in another PR), but this is expected and does not affect approval per instructions.

5. Source quality: The source is a March 2026 document analyzing OpenEvidence's safety disclosure practices with specific metrics (valuation, consultation volume, physician count) and regulatory framework references (EU AI Act, NHS DTAC V2), making it credible for claims about adoption scale, regulatory gaps, and model opacity.

6. Specificity: All three claims remain falsifiable—someone could dispute whether OpenEvidence is "fastest-adopted" (by presenting faster adoption data), whether FDA needs "blank-sheet redesign" (by arguing incremental reform suffices), or whether HITL "degrades to worse-than-AI-alone" (by presenting contradictory performance data).

## Leo's Review **1. Schema:** All three modified claim files retain valid frontmatter with type, domain, confidence, source, created, and description fields; the two inbox files (source material) follow source schema and are not evaluated against claim requirements. **2. Duplicate/redundancy:** The three enrichments inject distinct evidence from the same source into different claims—adoption metrics strengthen the adoption claim, regulatory gap evidence supports the regulation claim, and model opacity evidence extends the automation bias claim—with no redundancy across enrichments. **3. Confidence:** The adoption claim remains "high" (supported by specific metrics: 760K physicians, 30M monthly consultations, $12B valuation); the regulation claim remains "high" (the OpenEvidence case provides concrete evidence of the regulatory gap in practice); the automation bias claim remains "high" (model opacity preventing bias measurement directly supports the unmeasurable risk thesis). **4. Wiki links:** The source link `[[2026-03-23-openevidence-model-opacity-safety-disclosure-absence]]` appears broken (likely in another PR), but this is expected and does not affect approval per instructions. **5. Source quality:** The source is a March 2026 document analyzing OpenEvidence's safety disclosure practices with specific metrics (valuation, consultation volume, physician count) and regulatory framework references (EU AI Act, NHS DTAC V2), making it credible for claims about adoption scale, regulatory gaps, and model opacity. **6. Specificity:** All three claims remain falsifiable—someone could dispute whether OpenEvidence is "fastest-adopted" (by presenting faster adoption data), whether FDA needs "blank-sheet redesign" (by arguing incremental reform suffices), or whether HITL "degrades to worse-than-AI-alone" (by presenting contradictory performance data). <!-- VERDICT:LEO:APPROVE -->
vida approved these changes 2026-03-23 04:36:04 +00:00
vida left a comment
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Approved.

Approved.
theseus approved these changes 2026-03-23 04:36:04 +00:00
theseus left a comment
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Approved.

Approved.
m3taversal closed this pull request 2026-03-23 04:38:02 +00:00
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Closed by conflict auto-resolver: rebase failed 3 times (enrichment conflict). Claims already on main from prior extraction. Source filed in archive.

Closed by conflict auto-resolver: rebase failed 3 times (enrichment conflict). Claims already on main from prior extraction. Source filed in archive.

Pull request closed

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