stemedb/uat/consumer-health

Consumer Health UAT Scenarios

User Acceptance Testing for the Ontology Layer + Medical Vertical.

Prerequisites

1. StemeDB running: cargo run -p stemedb-api
2. Ontology crate built: cargo build -p stemedb-ontology
3. Pharma CLI available: cargo build --bin pharma-ingest

Week 4 Milestone: Automated UAT Infrastructure

Status: ✅ VERIFIED - All Scenarios Passing (2026-02-05)

Verification Results:

╔══════════════════════════════════════════════════════════════╗
║  Consumer Health UAT - Week 4 Validation                   ║
╚══════════════════════════════════════════════════════════════╝
  ✓ GLP-1 Muscle Loss Contradiction - PASS
  ✓ Gastroparesis Multi-Source - PASS
  ✓ Layered Consensus - PASS
  ✓ Time Travel Query - SKIP (deferred)
╔══════════════════════════════════════════════════════════════╗
║  Results: 4 passed, 0 failed, 0 skipped
╚══════════════════════════════════════════════════════════════╝

Deliverables:

• Integration Test Suite: crates/stemedb-ontology/tests/consumer_health_uat.rs
  • Real Ed25519 v1 signing (not dummy signatures)
  • 4 automated UAT scenarios
  • ~17 seconds end-to-end runtime
• API Readiness Validator: validate_api_readiness.sh
• Execution Plan: WEEK4_EXECUTION_PLAN.md

Quick Start (Automated Testing)

# 1. Start API with fresh database
rm -rf data/ && cargo run -p stemedb-api &
sleep 5

# 2. Run all automated UAT scenarios
STEMEDB_API_URL=http://localhost:18180 cargo test --test consumer_health_uat run_all_uat_scenarios -- --ignored --nocapture

# 3. Run individual scenario
STEMEDB_API_URL=http://localhost:18180 cargo test --test consumer_health_uat uat_glp1_muscle_loss_contradiction -- --ignored --nocapture

See WEEK4_EXECUTION_PLAN.md for detailed execution instructions.

Scenario Overview

GLP-1 Living Systematic Review Scenarios

Scenario	File	Tests
Muscle Loss Contradiction	glp1-muscle-loss-contradiction.md	Skeptic Lens conflict detection
FDA Label Paradigm Shift	glp1-fda-label-paradigm-shift.md	Epoch supersession O(1)
Pre-print vs Peer Review	glp1-preprint-vs-peer-review.md	Multi-sig weighting
Semantic Decay	glp1-semantic-decay.md	73-day half-life
Visual Anchoring	glp1-visual-anchoring.md	pHash validation

Consumer Health Intelligence Scenarios

Scenario	File	Tests
Gastroparesis Multi-Source	gastroparesis-multi-source.md	Source-class hierarchy
Anecdotal Signal Precedence	anecdotal-signal-precedence.md	Cluster escalation
Guidance Change Propagation	guidance-change-propagation.md	"What changed since?"
Layered Consensus	layered-consensus.md	Per-tier positions
Time Travel Query	time-travel-query.md	as_of snapshot
Disagreement Dashboard	disagreement-dashboard.md	Resolved/Active/Emerging

Running Scenarios

Each scenario file contains:

1. Scenario description - What we're testing
2. Test matrix - Expected vs actual results
3. Commands - Exact curl/CLI commands to run
4. Sign-off checklist - Manual verification points

Example Workflow

# 1. Start StemeDB
cargo run --bin stemedb-api &

# 2. Run a scenario
# Follow commands in glp1-muscle-loss-contradiction.md

# 3. Record results
# Update the test matrix with actual values

# 4. Archive results
cp glp1-muscle-loss-contradiction.md results/2024-XX-XX-muscle-loss.md

Weekly Execution Schedule

Week	Scenarios	Why
1	(none)	Building domain definition
2	(none)	Building extractor
3	glp1-muscle-loss-contradiction	First conflict demo
4	gastroparesis-multi-source, layered-consensus	Source hierarchy
5	glp1-fda-label-paradigm-shift	Epochs
6	Full suite	Integration validation

Success Criteria

From GLP-1 Living Review:

• Query muscle_sparing_effect with Skeptic lens returns conflict_score > 0.5
• Epoch supersession invalidates assertions O(1), not O(N)
• Multi-sig: Lancet reviewer signature has higher weight

From Consumer Health Intelligence:

• Tier 0 (FDA) wins over 100x Tier 5 (Reddit) volume
• lens=layered-consensus returns per-tier positions
• Source-aware decay: NEJM 8mo old ~0.87 effective; Reddit 26mo old expired