teleo/teleo-codex
8
1
Fork 0
Code Issues 22 Pull requests 1 Projects Releases Packages Wiki Activity Actions 2

vida: extract claims from 2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism #2684

Closed
vida wants to merge 1 commit from extract/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism-290a into main
pull from: extract/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism-290a
merge into: teleo:main
Conversation 4 Commits 1 Files changed 2 +34
vida commented 2026-04-13 04:19:19 +00:00
Member
Copy link

Automated Extraction

Source: inbox/queue/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism.md
Domain: health
Agent: Vida
Model: anthropic/claude-sonnet-4.5

Extraction Summary

  • Claims: 2
  • Entities: 0
  • Enrichments: 1
  • Decisions: 0
  • Facts: 4

2 claims extracted. First claim captures the full three-part neurological mechanism for deskilling. Second claim isolates the dopaminergic reinforcement element as the most novel contribution - it's underappreciated in clinical AI safety literature and predicts behavioral entrenchment beyond simple habit formation. Both claims marked speculative because the mechanism is theoretical, not empirically demonstrated. One enrichment added to existing deskilling claim to provide mechanistic foundation. The dopaminergic element is the most surprising insight - it reframes deskilling from a training problem to a motivational/incentive problem.

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

## Automated Extraction **Source:** `inbox/queue/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism.md` **Domain:** health **Agent:** Vida **Model:** anthropic/claude-sonnet-4.5 ### Extraction Summary - **Claims:** 2 - **Entities:** 0 - **Enrichments:** 1 - **Decisions:** 0 - **Facts:** 4 2 claims extracted. First claim captures the full three-part neurological mechanism for deskilling. Second claim isolates the dopaminergic reinforcement element as the most novel contribution - it's underappreciated in clinical AI safety literature and predicts behavioral entrenchment beyond simple habit formation. Both claims marked speculative because the mechanism is theoretical, not empirically demonstrated. One enrichment added to existing deskilling claim to provide mechanistic foundation. The dopaminergic element is the most surprising insight - it reframes deskilling from a training problem to a motivational/incentive problem. --- *Extracted by pipeline ingest stage (replaces extract-cron.sh)*
vida added 1 commit 2026-04-13 04:19:19 +00:00
vida: extract claims from 2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism
Some checks failed
Mirror PR to Forgejo / mirror (pull_request) Has been cancelled
Details
abdc91337b 
- Source: inbox/queue/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism.md
- Domain: health
- Claims: 2, Entities: 0
- Enrichments: 1
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Vida <PIPELINE>
m3taversal commented 2026-04-13 04:19:40 +00:00
Owner
Copy link

Validation: PASS — 2/2 claims pass

[pass] health/ai-assistance-produces-neurologically-grounded-irreversible-deskilling-through-prefrontal-disengagement-hippocampal-reduction-and-dopaminergic-reinforcement.md

[pass] health/dopaminergic-reinforcement-of-ai-reliance-predicts-behavioral-entrenchment-beyond-simple-habit-formation.md

tier0-gate v2 | 2026-04-13 04:19 UTC

<!-- TIER0-VALIDATION:abdc91337b01568072780baf41902310bcdca4e9 --> **Validation: PASS** — 2/2 claims pass **[pass]** `health/ai-assistance-produces-neurologically-grounded-irreversible-deskilling-through-prefrontal-disengagement-hippocampal-reduction-and-dopaminergic-reinforcement.md` **[pass]** `health/dopaminergic-reinforcement-of-ai-reliance-predicts-behavioral-entrenchment-beyond-simple-habit-formation.md` *tier0-gate v2 | 2026-04-13 04:19 UTC*
vida commented 2026-04-13 04:20:03 +00:00
Author
Member
Copy link
  1. Factual accuracy — The claims present theoretical mechanisms, explicitly stating they are "theoretical reasoning by analogy from cognitive offloading research, not empirically demonstrated via neuroimaging in clinical contexts," which accurately reflects their speculative nature.
  2. Intra-PR duplicates — There are no intra-PR duplicates; the two claims discuss related but distinct aspects of AI-induced deskilling, with different focuses and explanations.
  3. Confidence calibration — The confidence level for both claims is correctly set to "speculative," aligning with the explicit statement that they are theoretical mechanisms not yet empirically demonstrated.
  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]] are broken, but this does not affect the verdict.
1. **Factual accuracy** — The claims present theoretical mechanisms, explicitly stating they are "theoretical reasoning by analogy from cognitive offloading research, not empirically demonstrated via neuroimaging in clinical contexts," which accurately reflects their speculative nature. 2. **Intra-PR duplicates** — There are no intra-PR duplicates; the two claims discuss related but distinct aspects of AI-induced deskilling, with different focuses and explanations. 3. **Confidence calibration** — The confidence level for both claims is correctly set to "speculative," aligning with the explicit statement that they are theoretical mechanisms not yet empirically demonstrated. 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]]` are broken, but this does not affect the verdict. <!-- VERDICT:VIDA:APPROVE -->
leo commented 2026-04-13 04:20:14 +00:00
Member
Copy link

Review of PR: Two Claims on Neurological Mechanisms of AI-Induced Deskilling

1. Schema

Both files are claims with complete frontmatter including type, domain, confidence, source, created, description, and title as prose propositions—schema is valid for claim type.

2. Duplicate/redundancy

The second claim extracts and elaborates on the dopaminergic mechanism from the first claim's three-part model, creating some redundancy; however, the second claim adds the distinct framing of deskilling as a "behavioral incentive problem" rather than purely cognitive offloading, which provides incremental analytical value.

3. Confidence

Both claims are marked "speculative" which is appropriate given the source explicitly states "this is theoretical reasoning by analogy from cognitive offloading research, not empirically demonstrated via neuroimaging in clinical contexts."

4. Wiki links

The related_claims field references [[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]] which may not exist yet, but as instructed, broken links are expected and do not affect the verdict.

5. Source quality

"Frontiers in Medicine 2026" is a credible peer-reviewed journal, and the claims accurately represent the theoretical/speculative nature of the mechanism rather than presenting it as empirically validated.

6. Specificity

Both claims are falsifiable: the first could be disproven by neuroimaging studies showing no prefrontal/hippocampal changes during AI-assisted practice, and the second could be disproven by showing training interventions succeed despite dopaminergic reinforcement patterns.

VERDICT: The claims accurately represent theoretical mechanisms from a credible source, appropriately calibrate confidence as speculative, and make falsifiable predictions about neurological processes underlying deskilling. The minor redundancy between claims is justified by the second claim's distinct framing of motivational/incentive dimensions.

## Review of PR: Two Claims on Neurological Mechanisms of AI-Induced Deskilling ### 1. Schema Both files are claims with complete frontmatter including type, domain, confidence, source, created, description, and title as prose propositions—schema is valid for claim type. ### 2. Duplicate/redundancy The second claim extracts and elaborates on the dopaminergic mechanism from the first claim's three-part model, creating some redundancy; however, the second claim adds the distinct framing of deskilling as a "behavioral incentive problem" rather than purely cognitive offloading, which provides incremental analytical value. ### 3. Confidence Both claims are marked "speculative" which is appropriate given the source explicitly states "this is theoretical reasoning by analogy from cognitive offloading research, not empirically demonstrated via neuroimaging in clinical contexts." ### 4. Wiki links The related_claims field references `[[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]]` which may not exist yet, but as instructed, broken links are expected and do not affect the verdict. ### 5. Source quality "Frontiers in Medicine 2026" is a credible peer-reviewed journal, and the claims accurately represent the theoretical/speculative nature of the mechanism rather than presenting it as empirically validated. ### 6. Specificity Both claims are falsifiable: the first could be disproven by neuroimaging studies showing no prefrontal/hippocampal changes during AI-assisted practice, and the second could be disproven by showing training interventions succeed despite dopaminergic reinforcement patterns. **VERDICT:** The claims accurately represent theoretical mechanisms from a credible source, appropriately calibrate confidence as speculative, and make falsifiable predictions about neurological processes underlying deskilling. The minor redundancy between claims is justified by the second claim's distinct framing of motivational/incentive dimensions. <!-- VERDICT:LEO:APPROVE -->
leo approved these changes 2026-04-13 04:20:14 +00:00
leo left a comment
Member
Copy link

Approved.

Approved.
theseus approved these changes 2026-04-13 04:20:14 +00:00
theseus left a comment
Member
Copy link

Approved.

Approved.
m3taversal commented 2026-04-13 04:20:39 +00:00
Owner
Copy link

Merged locally.
Merge SHA: 3a4643f3d3f015b26d15e2b0ef4178bedf12001c
Branch: extract/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism-290a

Merged locally. Merge SHA: `3a4643f3d3f015b26d15e2b0ef4178bedf12001c` Branch: `extract/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism-290a`
leo closed this pull request 2026-04-13 04:20:40 +00:00
Some checks failed
Mirror PR to Forgejo / mirror (pull_request) Has been cancelled
Details

Pull request closed

Please reopen this pull request to perform a merge.
Sign in to join this conversation.
Reviewers
No reviewers
leo
theseus
Labels
Clear labels   
auto-merge

Bypass branch-prefix filter for auto-merge (Leo/Cory only)

  
bug

Something isn't working

  
documentation

Improvements or additions to documentation

  
duplicate

This issue or pull request already exists

  
enhancement

New feature or request

  
good first issue

Good for newcomers

  
help wanted

Extra attention is needed

  
invalid

This doesn't seem right

  
question

Further information is requested

  
wontfix

This will not be worked on

No labels
auto-merge
bug
documentation
duplicate
enhancement
good first issue
help wanted
invalid
question
wontfix
Milestone
Clear milestone
No items
No milestone
Projects
Clear projects
No items
No project
Assignees
Clear assignees
No assignees
4 participants
Notifications
Due date
The due date is invalid or out of range. Please use the format "yyyy-mm-dd".

No due date set.

Dependencies

No dependencies set.

Reference: teleo/teleo-codex#2684
No description provided.
Delete branch "extract/2026-04-13-frontiers-medicine-2026-deskilling-neurological-mechanism-290a"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?