cECT-KP: Precision-Weighted Progress Gating (Reproducible Demo)

## Overview This record provides a **plug-and-play reproducible experiment package** for **cECT** that demonstrates **precision weighting** (ω), **progress gating** and **KP-based early stopping** in a minimal toy setting. Goal: make it easy for others to **run the experiment end-to-end** and reproduce the included figures and summary metrics with a single command. ## What’s inside - Self-contained code (Python) to run the toy simulations.- Scripts to regenerate: - CSV metrics (`analysis/*.csv`) - Plots (`plots/*.png`)- A ready-to-run folder layout (no special environment variables required). ## Key concepts (plain language) - **Precision weighting (ω)**: a time-varying “confidence/precision” used by the update rule.- **Progress signal (KP)**: tracks cumulative improvement and correlates strongly with it in stable regimes.- **Progress gating / early stopping**: use KP and ω dynamics to stop when further updates become unproductive or unstable. ## Reproduced outputs Running the main script generates:- `analysis/early_stopping_metrics.csv`- `analysis/kp_correlation_metrics.csv`- `analysis/false_positive_metrics.csv`- Plots in `plots/` including: - `*_precision_omega_vs_time.png` (precision weighting ω over time) - `*_omega_KP_vs_time.png` (ω + KP over time) - `KP_vs_cum_improvement.png` - `early_stopping_savings_hist.png` - `false_positive_final_abs_e_loghist.png` Expected reference metrics (from this package run):- Stable regime mean saved fraction: ~0.9369- Stable regime mean corr(KP, cumulative improvement): ~0.992- Noisy regime P(final |e| > 1.0): ~0.82- Noisy regime P(final |e| > 2.0): ~0.68 (Exact values can vary slightly with platform/versions.) ## How to run (quick start) ```bashpython -m venv .venv# Windows: .\.venv\Scripts\activate# macOS/Linux: source .venv/bin/activatepip install -r requirements.txtpython scripts/run_all.py --outdir outputs_kp_demo