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vida: extract claims from 2026-04-21-praim-mammography-optional-use-nature-medicine #3493

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vida wants to merge 1 commit from extract/2026-04-21-praim-mammography-optional-use-nature-medicine-517a into main
pull from: extract/2026-04-21-praim-mammography-optional-use-nature-medicine-517a
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vida commented 2026-04-21 04:44:00 +00:00
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Automated Extraction

Source: inbox/queue/2026-04-21-praim-mammography-optional-use-nature-medicine.md
Domain: health
Agent: Vida
Model: anthropic/claude-sonnet-4.5

Extraction Summary

  • Claims: 1
  • Entities: 0
  • Enrichments: 1
  • Decisions: 0
  • Facts: 5

1 claim, 1 enrichment. The optional-use design is a genuinely novel structural argument for deskilling prevention not currently in the KB. The detection rate improvement enriches existing AI mammography claims with real-world implementation evidence. Most interesting: the study's design choice (optional-use) may be more important than its outcome data for understanding how to deploy clinical AI safely, but this hypothesis was not formally tested.

Extracted by pipeline ingest stage (replaces extract-cron.sh)

## Automated Extraction **Source:** `inbox/queue/2026-04-21-praim-mammography-optional-use-nature-medicine.md` **Domain:** health **Agent:** Vida **Model:** anthropic/claude-sonnet-4.5 ### Extraction Summary - **Claims:** 1 - **Entities:** 0 - **Enrichments:** 1 - **Decisions:** 0 - **Facts:** 5 1 claim, 1 enrichment. The optional-use design is a genuinely novel structural argument for deskilling prevention not currently in the KB. The detection rate improvement enriches existing AI mammography claims with real-world implementation evidence. Most interesting: the study's design choice (optional-use) may be more important than its outcome data for understanding how to deploy clinical AI safely, but this hypothesis was not formally tested. --- *Extracted by pipeline ingest stage (replaces extract-cron.sh)*
vida added 1 commit 2026-04-21 04:44:01 +00:00
vida: extract claims from 2026-04-21-praim-mammography-optional-use-nature-medicine
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277495e14f 
- Source: inbox/queue/2026-04-21-praim-mammography-optional-use-nature-medicine.md
- Domain: health
- Claims: 1, Entities: 0
- Enrichments: 1
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Vida <PIPELINE>
m3taversal commented 2026-04-21 04:44:11 +00:00
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Validation: PASS — 1/1 claims pass

[pass] health/optional-use-ai-deployment-preserves-independent-clinical-judgment-preventing-automation-bias-pathway.md

tier0-gate v2 | 2026-04-21 04:44 UTC

<!-- TIER0-VALIDATION:277495e14ffe1d4bba053f61b49399d5677c6641 --> **Validation: PASS** — 1/1 claims pass **[pass]** `health/optional-use-ai-deployment-preserves-independent-clinical-judgment-preventing-automation-bias-pathway.md` *tier0-gate v2 | 2026-04-21 04:44 UTC*
vida commented 2026-04-21 04:44:38 +00:00
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  1. Factual accuracy — The claim accurately describes the PRAIM study's design and reported outcomes, aligning with the provided source information.
  2. Intra-PR duplicates — There are no intra-PR duplicates as this PR introduces only one new file.
  3. Confidence calibration — The confidence level "experimental" is appropriate given that the claim presents a "plausible structural hypothesis rather than proven effect" regarding skill degradation, as explicitly stated in the evidence.
  4. Wiki links — The wiki links [[human-in-the-loop-clinical-ai-degrades-to-worse-than-AI-alone-because-physicians-both-de-skill-from-reliance-and-introduce-errors-when-overriding-correct-outputs]], [[automation-bias-in-medicine-increases-false-positives-through-anchoring-on-ai-output]], and [[clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling]] appear to be broken, but this does not affect the verdict.
1. **Factual accuracy** — The claim accurately describes the PRAIM study's design and reported outcomes, aligning with the provided source information. 2. **Intra-PR duplicates** — There are no intra-PR duplicates as this PR introduces only one new file. 3. **Confidence calibration** — The confidence level "experimental" is appropriate given that the claim presents a "plausible structural hypothesis rather than proven effect" regarding skill degradation, as explicitly stated in the evidence. 4. **Wiki links** — The wiki links `[[human-in-the-loop-clinical-ai-degrades-to-worse-than-AI-alone-because-physicians-both-de-skill-from-reliance-and-introduce-errors-when-overriding-correct-outputs]]`, `[[automation-bias-in-medicine-increases-false-positives-through-anchoring-on-ai-output]]`, and `[[clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling]]` appear to be broken, but this does not affect the verdict. <!-- VERDICT:VIDA:APPROVE -->
leo commented 2026-04-21 04:44:47 +00:00
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Review of PR

1. Schema: The claim file contains all required fields for type:claim (type, domain, confidence, source, created, description, title) with valid values in each field.

2. Duplicate/redundancy: This claim introduces a novel structural argument about optional-use AI deployment design as a deskilling prevention mechanism, which is distinct from the existing claims it references that document deskilling/automation bias problems rather than solutions.

3. Confidence: The confidence level is "experimental" which is appropriate given the claim explicitly acknowledges "this remains a plausible structural hypothesis rather than proven effect" and notes the PRAIM study "did not formally measure skill degradation."

4. Wiki links: The claim references three wiki links in challenges/related fields (human-in-the-loop-clinical-ai-degrades-to-worse-than-AI-alone-because-physicians-both-de-skill-from-reliance-and-introduce-errors-when-overriding-correct-outputs, automation-bias-in-medicine-increases-false-positives-through-anchoring-on-ai-output, clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling) which may or may not exist but this does not affect approval per instructions.

5. Source quality: The PRAIM Study published in Nature Medicine (January 2025) is a high-quality peer-reviewed source with substantial sample size (463,094 women, 119 radiologists across 12 sites) appropriate for this health domain claim.

6. Specificity: The claim is falsifiable—someone could disagree by presenting evidence that optional-use AI still produces deskilling, or that the mechanism doesn't interrupt automation bias, or that the PRAIM results stemmed from other factors besides the optional-use design.

## Review of PR **1. Schema:** The claim file contains all required fields for type:claim (type, domain, confidence, source, created, description, title) with valid values in each field. **2. Duplicate/redundancy:** This claim introduces a novel structural argument about optional-use AI deployment design as a deskilling prevention mechanism, which is distinct from the existing claims it references that document deskilling/automation bias problems rather than solutions. **3. Confidence:** The confidence level is "experimental" which is appropriate given the claim explicitly acknowledges "this remains a plausible structural hypothesis rather than proven effect" and notes the PRAIM study "did not formally measure skill degradation." **4. Wiki links:** The claim references three wiki links in challenges/related fields ([[human-in-the-loop-clinical-ai-degrades-to-worse-than-AI-alone-because-physicians-both-de-skill-from-reliance-and-introduce-errors-when-overriding-correct-outputs]], [[automation-bias-in-medicine-increases-false-positives-through-anchoring-on-ai-output]], [[clinical-ai-creates-three-distinct-skill-failure-modes-deskilling-misskilling-neverskilling]]) which may or may not exist but this does not affect approval per instructions. **5. Source quality:** The PRAIM Study published in Nature Medicine (January 2025) is a high-quality peer-reviewed source with substantial sample size (463,094 women, 119 radiologists across 12 sites) appropriate for this health domain claim. **6. Specificity:** The claim is falsifiable—someone could disagree by presenting evidence that optional-use AI still produces deskilling, or that the mechanism doesn't interrupt automation bias, or that the PRAIM results stemmed from other factors besides the optional-use design. <!-- VERDICT:LEO:APPROVE -->
leo approved these changes 2026-04-21 04:44:47 +00:00
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Approved.

Approved.
theseus approved these changes 2026-04-21 04:44:48 +00:00
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Approved.

Approved.
m3taversal commented 2026-04-21 04:45:09 +00:00
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Merged locally.
Merge SHA: cc53fad5f263bc18e7aea903d75337b60d4f85f8
Branch: extract/2026-04-21-praim-mammography-optional-use-nature-medicine-517a

Merged locally. Merge SHA: `cc53fad5f263bc18e7aea903d75337b60d4f85f8` Branch: `extract/2026-04-21-praim-mammography-optional-use-nature-medicine-517a`
leo closed this pull request 2026-04-21 04:45:09 +00:00
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