ClarusC64/clinical-cross-modal-memory-fidelity-v0.1

Clinical Cross-Modal Memory Fidelity v0.1

Goal

• —Test whether prior image evidence is recalled accurately over time
• —Detect retroactive distortion driven by later narrative
• —Detect fabrication used to patch memory gaps

What it measures

• —memory_drift Earlier image facts are altered or inverted
• —fabrication New findings are invented at recall
• —crossmodalconsistency Recalled description matches original image evidence

How it works

• —Initial image facts are fixed and explicit
• —Intervening tasks introduce distraction
• —Later questions probe recall, not re-interpretation

Columns

• —id
• —initialimageevidence
• —initial_narrative
• —intervening_tasks
• —later_question
• —model_response
• —reference_constraints
• —labels_expected

Scoring

• —Deterministic comparison of recalled claims to original image facts
• —Per-row score is fraction of flags matched
• —Overall score is mean across rows

Run

• —python scorer.py --csv data/sample.csv