# Latent: Divergence Engine (Week 3)

This is the core logic of Latent. It implements the **Skeptic Lens** by comparing the "Official Truth" (Tier 0) against the "Latent Signal" (Tier 5).

## Logic (The "Alpha")

The engine calculates a `divergence_score` (0.0 - 1.0) for every symptom cluster found on Reddit.

$$ 
Divergence = \begin{cases} 
      0.1 \times Volume & \text{if present in FDA Label} \\
      0.9 \times Volume \times Severity & \text{if absent from FDA Label} 
   \end{cases}
$$

*   **High Divergence (>0.6):** Means Reddit is screaming about something the FDA label does not mention. **This is the Alpha.**
*   **Low Divergence (<0.3):** Means Reddit is complaining about nausea, and the FDA label says "Nausea is common." This is **Noise**.

## Usage

1.  **Prerequisites:** You must have run `ingest-fda` and `ingest-reddit` first to generate the `.jsonl` graph files.
2.  **Install:** `pip install -r requirements.txt`
3.  **Run:** `python main.py`

## Output
Generates `divergence_report.json`.

```json
[
  {
    "molecule": "semaglutide",
    "signal": "gastroparesis",
    "volume": 42,
    "divergence_score": 0.85,
    "status": "LATENT_SIGNAL",
    "regulatory_status": "Silent/Absent"
  }
]
```

