stemedb/latent/divergence-engine

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.

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