Energetic Efficiency of Two-Stage Wave–Commitment Decision Architecture: Data, Code, and Figures

Dataset, analysis code, and figures accompanying the preprint "Energetic Efficiency of Two-Stage Wave–Commitment Decision Architecture: A Meta-Analytic Comparison with Drift-Diffusion Models" (Dolgikh, 2026; doi:10.5281/zenodo.18785552). Contents:— 7 CSV data files: β_crit parameter sweeps (480 rows), sensitivity analysis, urgency-gating calibration, and a hardened meta-analysis of 25 published DDM task conditions from 11 sources.— 3 Python scripts (v12d, v12e, v13b): fully self-contained, reproduce all results and figures from scratch.— 3 multi-panel figures (phase diagrams, UG comparison, meta-analysis).— PRISMA search protocol (v13b_mini_prisma.md).— SHA-256 manifest for integrity verification. All DDM parameters use σ=0.1 (Ratcliff convention), boundaries 0..a. Energy proxy = decision time (ms). UG speedup = 1.07× (Monte Carlo calibrated). Requirements: Python ≥3.11, NumPy ≥1.26, SciPy ≥1.12, Matplotlib ≥3.8.