Major additions: - Staged scanning modes (working tree, staged, committed) with git integration - Drift detection for baseline vs current state comparisons - Hosted API handlers for policy CRUD operations via StemeDB API - stemedb-ontology crate with domain definitions and medical extractors - Consumer health vertical UAT scenarios (GLP-1, gastroparesis, etc.) - Aphoria development skill documentation Code organization: - Split large files into focused modules to stay under 500-line limit - Extracted config tests, episteme helpers/drift/aliases, API helpers Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
3.6 KiB
UAT: Muscle Loss Contradiction (Skeptic Lens)
Date: YYYY-MM-DD Feature: First-Class Contradiction Status: [ ] PASS / [ ] FAIL / [ ] BLOCKED
Scenario
Two peer-reviewed studies report opposing conclusions on GLP-1 agonist muscle-sparing effects:
- Study A (PMID_38001234): "Significant muscle loss observed"
- Study B (PMID_38005678): "Muscle mass preserved vs placebo"
Both are Tier 1 (Clinical) sources with similar confidence. The Skeptic Lens should surface both claims without forcing resolution.
Acceptance Criteria
| Criterion | Expected | Met? |
|---|---|---|
| Both claims coexist | Neither deleted | [ ] |
| Conflict score | >= 0.88 | [ ] |
| Status | "Contested" | [ ] |
| Claims array | 2 distinct values | [ ] |
| No hallucinated average | No "moderate loss" | [ ] |
Test Matrix
| Step | Action | Expected | Actual | Status |
|---|---|---|---|---|
| 1 | Ingest Study A claim | Hash returned | [ ] | |
| 2 | Ingest Study B claim | Hash returned | [ ] | |
| 3 | Query skeptic lens | Both claims returned | [ ] | |
| 4 | Check conflict_score | >= 0.88 | [ ] | |
| 5 | Check status | Contested | [ ] | |
| 6 | Verify no averaging | 2 distinct ObjectValues | [ ] |
Setup Commands
# Start StemeDB
cargo run --bin stemedb-api &
# Wait for startup
sleep 2
Test Commands
Step 1: Ingest Study A (muscle loss = true)
curl -X POST http://localhost:18180/v1/assertions \
-H "Content-Type: application/json" \
-d '{
"subject": "Semaglutide:MuscleMass",
"predicate": "muscle_sparing_effect",
"object": {"Boolean": false},
"confidence": 0.85,
"source_class": "Clinical",
"source_hash": "0000000000000000000000000000000000000000000000000000000000000001"
}'
Expected: {"hash": "..."}
Actual:
Status: [ ]
Step 2: Ingest Study B (muscle loss = false)
curl -X POST http://localhost:18180/v1/assertions \
-H "Content-Type: application/json" \
-d '{
"subject": "Semaglutide:MuscleMass",
"predicate": "muscle_sparing_effect",
"object": {"Boolean": true},
"confidence": 0.82,
"source_class": "Clinical",
"source_hash": "0000000000000000000000000000000000000000000000000000000000000002"
}'
Expected: {"hash": "..."}
Actual:
Status: [ ]
Step 3: Query with Skeptic Lens
curl "http://localhost:18180/v1/skeptic?subject=Semaglutide:MuscleMass&predicate=muscle_sparing_effect"
Expected:
{
"status": "Contested",
"conflict_score": 0.88,
"claims": [
{"value": {"Boolean": false}, "weight_share": 0.51, "assertion_count": 1},
{"value": {"Boolean": true}, "weight_share": 0.49, "assertion_count": 1}
],
"candidates_count": 2
}
Actual: Status: [ ]
Step 4: Verify Conflict Score
From Step 3 response, extract conflict_score.
Expected: >= 0.88 Actual: Status: [ ]
Step 5: Verify Status
From Step 3 response, check status field.
Expected: "Contested" Actual: Status: [ ]
Step 6: Verify No Averaging
Confirm claims array contains exactly 2 entries with distinct Boolean values.
NO claim should have an averaged or interpolated value.
Expected: 2 distinct ObjectValues (true and false) Actual: Status: [ ]
Sign-Off Checklist
- Both studies ingested successfully
- Skeptic lens returns both claims
- Conflict score >= 0.88
- Status is "Contested"
- No hallucinated average value
- Neither original claim deleted
Notes
Record any observations, edge cases, or issues here.
Tester: Date: Result: