Self Validation Loop

Self-Validation Loop

Use when training or evaluating self-validation for 3-stream color systems.

Inputs

• seed, indices
• sources: splitmix_ternary, xoroshiro_3color, gay_mcp
• comparator: reafference or comparator

Workflow

1. Predict expected colors (efference copy).
2. Observe actual colors (color_at or stream generation).
3. Compare predictions with observations.
4. Aggregate accuracy and surprise.

Gay MCP tools

• gay_seed, efference_copy, color_at, reafference, comparator, active_inference, self_model

Metrics

• accuracy = matches / total
• surprise = mismatch count or summed error
• pass threshold: accuracy >= 0.99 or surprise == 0

Output

• JSON log with seed, indices, predicted, observed, errors, accuracy, surprise

Example prompt

"Run a self-validation loop over indices 1..20 and report accuracy and surprise."

Scientific Skill Interleaving

This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:

Graph Theory

• networkx [○] via bicomodule
  • Universal graph hub

Bibliography References

• general: 734 citations in bib.duckdb

Cat# Integration

This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:

Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826

GF(3) Naturality

The skill participates in triads satisfying:

(-1) + (0) + (+1) ≡ 0 (mod 3)

This ensures compositional coherence in the Cat# equipment structure.