# UAT: Pre-print vs Peer Review (Multi-Sig Weighting)

**Date:** YYYY-MM-DD
**Feature:** Multi-Signature Consensus
**Status:** [ ] PASS / [ ] FAIL / [ ] BLOCKED

## Scenario

A pre-print on bioRxiv claims GLP-1 drugs have cardiovascular risks. A peer-reviewed Lancet study with expert co-signatures says cardiovascular outcomes are improved.

The system should weight the Lancet study higher due to:
1. Higher source class (Clinical vs Observational)
2. Co-signatures from recognized reviewers

## Acceptance Criteria

| Criterion | Expected | Met? |
|-----------|----------|------|
| Pre-print ingested | Hash returned | [ ] |
| Peer-reviewed ingested | Hash returned | [ ] |
| Co-signatures applied | 3 signatures on Lancet | [ ] |
| Authority lens winner | Lancet study | [ ] |
| Weight differential | Lancet > 2x bioRxiv | [ ] |

## Test Matrix

| Step | Action | Expected | Actual | Status |
|------|--------|----------|--------|--------|
| 1 | Ingest bioRxiv pre-print | Hash returned | | [ ] |
| 2 | Ingest Lancet study | Hash returned | | [ ] |
| 3 | Add co-signatures to Lancet | 3 signatures recorded | | [ ] |
| 4 | Query with Authority lens | Lancet wins | | [ ] |
| 5 | Check weight ratio | >= 2x | | [ ] |

## Setup Commands

```bash
# Start StemeDB
cargo run --bin stemedb-api &
sleep 2
```

## Test Commands

### Step 1: Ingest bioRxiv Pre-print (Observational, no co-signs)

```bash
curl -X POST http://localhost:18180/v1/assertions \
  -H "Content-Type: application/json" \
  -d '{
    "subject": "Semaglutide:CardiovascularOutcome",
    "predicate": "cv_risk_change",
    "object": {"Number": 1.15},
    "confidence": 0.65,
    "source_class": "Observational",
    "source_hash": "0000000000000000000000000000000000000000000000000000000000000010"
  }'
```

**Expected:** `{"hash": "..."}`
**Actual:**
**Status:** [ ]

### Step 2: Ingest Lancet Study (Clinical, peer-reviewed)

```bash
curl -X POST http://localhost:18180/v1/assertions \
  -H "Content-Type: application/json" \
  -d '{
    "subject": "Semaglutide:CardiovascularOutcome",
    "predicate": "cv_risk_change",
    "object": {"Number": 0.86},
    "confidence": 0.92,
    "source_class": "Clinical",
    "source_hash": "0000000000000000000000000000000000000000000000000000000000000011"
  }'
```

Save the returned hash as `<LANCET_HASH>`.

**Expected:** `{"hash": "..."}`
**Actual:**
**Status:** [ ]

### Step 3: Add Co-Signatures to Lancet Study

```bash
# Expert reviewer 1
curl -X POST http://localhost:18180/v1/votes \
  -H "Content-Type: application/json" \
  -d '{
    "assertion_hash": "<LANCET_HASH>",
    "agent_id": "expert_cardiologist_001",
    "weight": 0.95
  }'

# Expert reviewer 2
curl -X POST http://localhost:18180/v1/votes \
  -H "Content-Type: application/json" \
  -d '{
    "assertion_hash": "<LANCET_HASH>",
    "agent_id": "expert_cardiologist_002",
    "weight": 0.90
  }'

# Lancet editor
curl -X POST http://localhost:18180/v1/votes \
  -H "Content-Type: application/json" \
  -d '{
    "assertion_hash": "<LANCET_HASH>",
    "agent_id": "lancet_editor_review",
    "weight": 0.85
  }'
```

**Expected:** 3 votes recorded
**Actual:**
**Status:** [ ]

### Step 4: Query with Authority Lens

```bash
curl "http://localhost:18180/v1/query?subject=Semaglutide:CardiovascularOutcome&predicate=cv_risk_change&lens=authority"
```

**Expected:** Winner is Lancet study (cv_risk_change = 0.86)
**Actual:**
**Status:** [ ]

### Step 5: Verify Weight Differential

Query the skeptic lens to see weight shares:

```bash
curl "http://localhost:18180/v1/skeptic?subject=Semaglutide:CardiovascularOutcome&predicate=cv_risk_change"
```

**Expected:** Lancet weight_share >= 2x bioRxiv weight_share
**Actual:**
**Status:** [ ]

## Sign-Off Checklist

- [ ] Pre-print assertion stored correctly
- [ ] Peer-reviewed assertion stored correctly
- [ ] Co-signatures increase effective weight
- [ ] Authority lens prefers higher-tier + more signatures
- [ ] Weight differential is meaningful (>= 2x)

## Notes

*Multi-sig validation happens via VoteStore aggregation, not signature count alone.*

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**Tester:**
**Date:**
**Result:**