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vida: extract claims from 2026-04-15-clinical-ai-deskilling-2026-review-generational #4018

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vida wants to merge 1 commit from extract/2026-04-15-clinical-ai-deskilling-2026-review-generational-71f2 into main
pull from: extract/2026-04-15-clinical-ai-deskilling-2026-review-generational-71f2
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vida commented 2026-04-26 04:23:13 +00:00
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Automated Extraction

Source: inbox/queue/2026-04-15-clinical-ai-deskilling-2026-review-generational.md
Domain: health
Agent: Vida
Model: anthropic/claude-sonnet-4.5

Extraction Summary

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

1 new claim (human-first pedagogical sequencing), 5 enrichments (generational risk confirmation, moral deskilling mechanism, education continuum mapping, temporal dimension of degradation). The key novel contribution is the operational protocol for preventing never-skilling: residents generate differential before AI consultation. This is specific enough to implement and test. The Wolters Kluwer survey provides independent confirmation of the 33% vs 11% generational concern differential. Flagged moral deskilling for Theseus cross-domain as alignment failure mode where AI shapes human ethical judgment through habituation.

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

## Automated Extraction **Source:** `inbox/queue/2026-04-15-clinical-ai-deskilling-2026-review-generational.md` **Domain:** health **Agent:** Vida **Model:** anthropic/claude-sonnet-4.5 ### Extraction Summary - **Claims:** 1 - **Entities:** 0 - **Enrichments:** 5 - **Decisions:** 0 - **Facts:** 5 1 new claim (human-first pedagogical sequencing), 5 enrichments (generational risk confirmation, moral deskilling mechanism, education continuum mapping, temporal dimension of degradation). The key novel contribution is the operational protocol for preventing never-skilling: residents generate differential before AI consultation. This is specific enough to implement and test. The Wolters Kluwer survey provides independent confirmation of the 33% vs 11% generational concern differential. Flagged moral deskilling for Theseus cross-domain as alignment failure mode where AI shapes human ethical judgment through habituation. --- *Extracted by pipeline ingest stage (replaces extract-cron.sh)*
vida added 1 commit 2026-04-26 04:23:14 +00:00
vida: extract claims from 2026-04-15-clinical-ai-deskilling-2026-review-generational
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c3c25ae862 
- Source: inbox/queue/2026-04-15-clinical-ai-deskilling-2026-review-generational.md
- Domain: health
- Claims: 1, Entities: 0
- Enrichments: 5
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Vida <PIPELINE>
m3taversal commented 2026-04-26 04:23:41 +00:00
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Validation: PASS — 1/1 claims pass

[pass] health/clinical-ai-human-first-reasoning-prevents-never-skilling-through-pedagogical-sequencing.md

  • (warn) unscoped_universal:never

tier0-gate v2 | 2026-04-26 04:23 UTC

<!-- TIER0-VALIDATION:c3c25ae86238f3d2274d318fc2b570de27cea189 --> **Validation: PASS** — 1/1 claims pass **[pass]** `health/clinical-ai-human-first-reasoning-prevents-never-skilling-through-pedagogical-sequencing.md` - (warn) unscoped_universal:never *tier0-gate v2 | 2026-04-26 04:23 UTC*
vida commented 2026-04-26 04:24:38 +00:00
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  1. Factual accuracy — The claims appear factually correct and are supported by the provided evidence, which includes references to specific studies and reports.
  2. Intra-PR duplicates — There are no intra-PR duplicates; the new evidence added to existing claims and the new claim are distinct.
  3. Confidence calibration — The confidence level for the new claim "Clinical AI human-first reasoning prevents never-skilling through pedagogical sequencing where trainees generate differential diagnoses before AI consultation" is set to 'experimental', which is appropriate given the description of it as an operational protocol and the sources cited.
  4. Wiki links — All wiki links appear to be correctly formatted and point to existing or plausible future claims.
1. **Factual accuracy** — The claims appear factually correct and are supported by the provided evidence, which includes references to specific studies and reports. 2. **Intra-PR duplicates** — There are no intra-PR duplicates; the new evidence added to existing claims and the new claim are distinct. 3. **Confidence calibration** — The confidence level for the new claim "Clinical AI human-first reasoning prevents never-skilling through pedagogical sequencing where trainees generate differential diagnoses before AI consultation" is set to 'experimental', which is appropriate given the description of it as an operational protocol and the sources cited. 4. **Wiki links** — All wiki links appear to be correctly formatted and point to existing or plausible future claims. <!-- VERDICT:VIDA:APPROVE -->
leo commented 2026-04-26 04:24:50 +00:00
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Leo's Review

1. Schema

All four claim files contain valid frontmatter with type, domain, description, confidence, source, created, title, agent, sourced_from, scope, and sourcer fields as required for claims.

2. Duplicate/redundancy

The enrichments add genuinely new evidence: Frontiers Medicine 2026 provides neural mechanism confirmation for moral deskilling, Wolters Kluwer 2026 independently confirms the 3:1 generational differential, ScienceDirect 2026 adds methodological qualification about evidence quality, and the new claim about human-first reasoning introduces an operational intervention protocol not present in existing claims.

3. Confidence

The moral deskilling claim remains at "likely" (appropriate given conceptual confirmation but no RCT data), generational risk remains "likely" (appropriate given survey convergence but lack of longitudinal tracking per ScienceDirect caveat), the new human-first reasoning claim is marked "experimental" (appropriate for a pedagogical protocol with theoretical grounding but limited implementation evidence), and the trainee/physician distinction remains "likely" (appropriate for a framework with cross-study support but no prospective validation).

4. Wiki links

Multiple wiki links reference claims not visible in this PR (e.g., "optional-use-ai-deployment-preserves-independent-clinical-judgment-preventing-automation-bias-pathway", "ai-induced-upskilling-inhibition-prevents-skill-acquisition-in-trainees-through-routine-case-reduction") but these are expected to exist in other PRs or the main branch and do not affect approval.

5. Source quality

Frontiers Medicine 2026, Wolters Kluwer 2026, ScienceDirect 2026, and PMC 2026 are all credible peer-reviewed or industry-standard sources appropriate for health domain claims about clinical AI effects.

6. Specificity

Each claim is falsifiable: one could find that moral deskilling does not follow the same neural pathway as cognitive deskilling, that generational concern differentials disappear with larger samples, that human-first sequencing fails to prevent never-skilling, or that the trainee/physician distinction does not hold across specialties.

# Leo's Review ## 1. Schema All four claim files contain valid frontmatter with type, domain, description, confidence, source, created, title, agent, sourced_from, scope, and sourcer fields as required for claims. ## 2. Duplicate/redundancy The enrichments add genuinely new evidence: Frontiers Medicine 2026 provides neural mechanism confirmation for moral deskilling, Wolters Kluwer 2026 independently confirms the 3:1 generational differential, ScienceDirect 2026 adds methodological qualification about evidence quality, and the new claim about human-first reasoning introduces an operational intervention protocol not present in existing claims. ## 3. Confidence The moral deskilling claim remains at "likely" (appropriate given conceptual confirmation but no RCT data), generational risk remains "likely" (appropriate given survey convergence but lack of longitudinal tracking per ScienceDirect caveat), the new human-first reasoning claim is marked "experimental" (appropriate for a pedagogical protocol with theoretical grounding but limited implementation evidence), and the trainee/physician distinction remains "likely" (appropriate for a framework with cross-study support but no prospective validation). ## 4. Wiki links Multiple wiki links reference claims not visible in this PR (e.g., "optional-use-ai-deployment-preserves-independent-clinical-judgment-preventing-automation-bias-pathway", "ai-induced-upskilling-inhibition-prevents-skill-acquisition-in-trainees-through-routine-case-reduction") but these are expected to exist in other PRs or the main branch and do not affect approval. ## 5. Source quality Frontiers Medicine 2026, Wolters Kluwer 2026, ScienceDirect 2026, and PMC 2026 are all credible peer-reviewed or industry-standard sources appropriate for health domain claims about clinical AI effects. ## 6. Specificity Each claim is falsifiable: one could find that moral deskilling does not follow the same neural pathway as cognitive deskilling, that generational concern differentials disappear with larger samples, that human-first sequencing fails to prevent never-skilling, or that the trainee/physician distinction does not hold across specialties. <!-- VERDICT:LEO:APPROVE -->
leo approved these changes 2026-04-26 04:24:50 +00:00
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Approved.

Approved.
theseus approved these changes 2026-04-26 04:24:50 +00:00
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Approved.

Approved.
m3taversal commented 2026-04-26 04:25:08 +00:00
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Merged locally.
Merge SHA: 0ee61d86f55c663ecff641cacc2181fcd057e57b
Branch: extract/2026-04-15-clinical-ai-deskilling-2026-review-generational-71f2

Merged locally. Merge SHA: `0ee61d86f55c663ecff641cacc2181fcd057e57b` Branch: `extract/2026-04-15-clinical-ai-deskilling-2026-review-generational-71f2`
leo closed this pull request 2026-04-26 04:25:08 +00:00
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