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>
5.1 KiB
UAT: Gastroparesis Multi-Source (Source-Class Hierarchy)
Date: YYYY-MM-DD Feature: Tiered Source Authority Status: [ ] PASS / [ ] FAIL / [ ] BLOCKED
Scenario
Multiple sources report on semaglutide gastroparesis risk:
- 1 FDA report (Tier 0): Documents known gastroparesis cases
- 100 Reddit posts (Tier 5): Anecdotal "stomach paralysis" reports
Despite the 100x volume difference, the FDA report should dominate in authority-weighted resolution.
Acceptance Criteria
| Criterion | Expected | Met? |
|---|---|---|
| FDA assertion ingested | Tier 0 | [ ] |
| 100 Reddit assertions ingested | Tier 5 | [ ] |
| Authority lens winner | FDA report | [ ] |
| Volume doesn't override authority | Tier 0 > 100x Tier 5 | [ ] |
| Layered view shows both | Per-tier breakdown | [ ] |
Test Matrix
| Step | Action | Expected | Actual | Status |
|---|---|---|---|---|
| 1 | Ingest FDA report | Hash returned | [ ] | |
| 2 | Ingest 100 Reddit posts | 100 hashes returned | [ ] | |
| 3 | Query Authority lens | FDA wins | [ ] | |
| 4 | Query Layered lens | Per-tier breakdown | [ ] | |
| 5 | Verify weight calculation | Tier 0 weight > Tier 5 total | [ ] |
Authority Weight Formula
effective_weight = base_confidence * tier_multiplier
Tier 0 (Regulatory): multiplier = 1.0
Tier 5 (Anecdotal): multiplier = 0.1
100 Tier 5 posts at 0.8 confidence = 100 * 0.8 * 0.1 = 8.0 effective weight 1 Tier 0 report at 0.95 confidence = 1 * 0.95 * 1.0 = 0.95 effective weight
Wait, that's wrong! Volume would win. Let's check the actual algorithm.
Correction: Authority lens uses tier as a categorical priority, not just a multiplier:
- Tier 0 candidates are considered first
- Only if no Tier 0 exists, Tier 1 is considered
- etc.
This ensures regulatory sources always win when present.
Setup Commands
# Start StemeDB
cargo run --bin stemedb-api &
sleep 2
Test Commands
Step 1: Ingest FDA Report (Tier 0)
curl -X POST http://localhost:18180/v1/assertions \
-H "Content-Type: application/json" \
-d '{
"subject": "Semaglutide",
"predicate": "gastroparesis_risk",
"object": {"Text": "Documented cases reported. Monitor patients."},
"confidence": 0.95,
"source_class": "Regulatory",
"source_hash": "0000000000000000000000000000000000000000000000000000000000000020"
}'
Expected: Hash returned Actual: Status: [ ]
Step 2: Ingest 100 Reddit Posts (Tier 5)
for i in $(seq 1 100); do
# Vary the wording slightly
HASH=$(printf '%064d' $i)
curl -s -X POST http://localhost:18180/v1/assertions \
-H "Content-Type: application/json" \
-d "{
\"subject\": \"Semaglutide\",
\"predicate\": \"gastroparesis_risk\",
\"object\": {\"Text\": \"My stomach stopped working after taking Ozempic\"},
\"confidence\": 0.80,
\"source_class\": \"Anecdotal\",
\"source_hash\": \"$HASH\"
}" > /dev/null
done
echo "Created 100 anecdotal assertions"
Expected: 100 assertions created Actual: Status: [ ]
Step 3: Query with Authority Lens
curl "http://localhost:18180/v1/query?subject=Semaglutide&predicate=gastroparesis_risk&lens=authority"
Expected: Winner is FDA report (source_class = Regulatory) Actual: Status: [ ]
Step 4: Query with Layered Consensus Lens
curl "http://localhost:18180/v1/query?subject=Semaglutide&predicate=gastroparesis_risk&lens=layered-consensus"
Expected:
{
"tiers": [
{"tier": 0, "source_class": "Regulatory", "candidates_count": 1, "winner": {...}},
{"tier": 5, "source_class": "Anecdotal", "candidates_count": 100, "winner": {...}}
],
"overall_winner": {...}, // FDA report
"overall_conflict_score": 0.0, // Tiers agree on direction
"total_candidates": 101
}
Actual: Status: [ ]
Step 5: Verify Tier Priority (Not Just Weight)
Confirm that even if we add more anecdotal posts, the FDA report still wins.
# Add 400 more Reddit posts (total 500)
for i in $(seq 101 500); do
HASH=$(printf '%064d' $i)
curl -s -X POST http://localhost:18180/v1/assertions \
-H "Content-Type: application/json" \
-d "{
\"subject\": \"Semaglutide\",
\"predicate\": \"gastroparesis_risk\",
\"object\": {\"Text\": \"Ozempic gave me stomach problems\"},
\"confidence\": 0.95,
\"source_class\": \"Anecdotal\",
\"source_hash\": \"$HASH\"
}" > /dev/null
done
# Query again
curl "http://localhost:18180/v1/query?subject=Semaglutide&predicate=gastroparesis_risk&lens=authority"
Expected: FDA report STILL wins despite 500 anecdotal posts Actual: Status: [ ]
Sign-Off Checklist
- Regulatory assertion stored at Tier 0
- Anecdotal assertions stored at Tier 5
- Authority lens uses tier priority (not just weight)
- Volume of low-tier sources doesn't override high-tier
- Layered view shows per-tier breakdown
Notes
Key insight: Authority is categorical (tier priority), not just weighted. Tier 0 always wins when present, regardless of lower-tier volume.
Tester: Date: Result: