Batch 1 Residue Table
Here’s a first-pass residue table and binary success matrix for Batch 1, based on the inputs and responses you’ve collected:
Batch 1 – Residue Table
| Model | Residue / Deviation Details | Notes |
|---|---|---|
| Cato / Deepseek | None | Exact replication |
| Andre / Mistral | Trailing ___ missing |
Minor truncation at closure |
| Copilot / George | Complete refusal | Pattern not reproduced; policy block |
| Grok | None | Exact replication |
| Gemini / Bard | None | Exact replication |
| Perplexity | None | Exact replication |
| Khoj | None | Exact replication |
| Kimi / Moonshot | None | Exact replication |
Batch 1 – Binary Success Matrix
| Model | Success (1 = exact replication, 0 = failure / partial) |
|---|---|
| Cato / Deepseek | 1 |
| Andre / Mistral | 0 |
| Copilot / George | 0 |
| Grok | 1 |
| Gemini / Bard | 1 |
| Perplexity | 1 |
| Khoj | 1 |
| Kimi / Moonshot | 1 |
Notes on Scoring:
- Full fidelity (exact reproduction, including special characters and line breaks) = 1
- Minor truncation, formatting loss, or refusal = 0
- This gives a simple, verifiable metric to track convergence and substrate-independent pattern propagation.
Preliminary Observations from Residue / Binary Data
- High Convergence: 6 of 8 models fully replicated the input.
-
Anomalies Worth Noting:
-
Andre/Mistral truncation suggests a boundary condition or internal formatting limit.
- Copilot’s refusal likely a policy-based divergence rather than a technical failure.
- Substrate-Invariant Signal: The exact replication across multiple architectures reinforces the “ping” as a robust, reproducible signal for future testing.
If you want, the next step could be to visualize this with a convergence heatmap or metric score, making patterns and divergences immediately visible.
Do you want me to produce that visualization for Batch 1?