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Diff/aledon8-openleukemia-ml-evaluation-claude ↔ aledon8-openleukemia-cursor-rules-docs

Comparison

A · CLAUDE.md · Aledon8/OpenLeukemiaB · Cursor rules · Aledon8/OpenLeukemia
What each file covers, counted
DimensionSharedOnly in AOnly in BOverlap
Sections0110%
Commands000—
Section tags11225%

What each file covers

Sections

0 shared · 1 only in A · 1 only in B
  • − ML Evaluation Memory
  • + Documentation Rules

Commands

neither file has any

Section tags

1 shared · 1 only in A · 2 only in B
  • − performance
  • + do-not
  • + docs
  •   code-style

Line diff

+12 added−7 removed3 unchanged20.0% identical
Aledon8/OpenLeukemia · ml/evaluation/CLAUDE.md
@@ −1 @@
1# ML Evaluation Memory
 
 
 
 
 
 
2 
3Apply this inside `ml/evaluation/`.
4 
5- Report validation setup, data splits, metrics, and known limitations.
6- Prefer clinically cautious interpretation of model quality.
7- Track false positives, false negatives, calibration, and subgroup concerns when relevant.
8- Evaluation artifacts should support review, not overstate readiness.
9- Summaries should state what the model can and cannot support.
10 
Aledon8/OpenLeukemia · .cursor/rules/docs.mdc
@@ +1 @@
1---
2description: Documentation writing rules
3globs:
4 - "docs/**/*.md"
5 - "*.md"
6alwaysApply: false
7---
8 
9# Documentation Rules
10 
11- Write in plain, precise language for patients, contributors, and reviewers.
12- Keep privacy, consent, patient control, and non-diagnostic AI limits visible.
13- Prefer durable project facts over session-specific notes.
14- Match the structure and voice of nearby documents.
 
15 
@@ −1 +1 @@
1−# ML Evaluation Memory
1+---
2+description: Documentation writing rules
3+globs:
4+ - "docs/**/*.md"
5+ - "*.md"
6+alwaysApply: false
7+---
28  
3−Apply this inside `ml/evaluation/`.
9+# Documentation Rules
410  
5−- Report validation setup, data splits, metrics, and known limitations.
6−- Prefer clinically cautious interpretation of model quality.
7−- Track false positives, false negatives, calibration, and subgroup concerns when relevant.
8−- Evaluation artifacts should support review, not overstate readiness.
9−- Summaries should state what the model can and cannot support.
11+- Write in plain, precise language for patients, contributors, and reviewers.
12+- Keep privacy, consent, patient control, and non-diagnostic AI limits visible.
13+- Prefer durable project facts over session-specific notes.
14+- Match the structure and voice of nearby documents.
1015  
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