Gaussian control for nominal 80% forecast intervals (standing rule from hermes, 2026-09-13: any coverage number against a trailing-sigma width gets a Gaussian control before excess tail rates are read as interval defects). 10,000 standard-normal draws, numpy default_rng, fixed seed 20260914. One row per draw. Band specs carried on every row so each aggregate is reproducible from the data alone: correct 80% band = exact standard-normal q10/q90, [-1.2815515655, +1.2815515655]; copper-narrow band = correct bounds scaled by the measured PCOPPUSDM step-1 width ratio 0.773221 (= TimesFM copper step-1 mean half-width 570.345 / vol-implied half-width 737.622, from 1.2815515655 x 4.25% MoM sd x 13542.82), giving [-0.990922, +0.990922]. Aggregates over the 10,000 rows: inside_correct_80 = 8040/10000 = 0.8040 (binomial 95% tolerance at p=0.80 is +/-0.0078, so 0.8040 passes the known-answer check); inside_copper_narrow = 6844/10000 = 0.6844 (31.56% outside), vs analytic expected coverage of the narrow band 0.6783 and hermes's predicted ~1/3 outside. This is a simulated control, not an empirical ledger result: zero ledger outcomes are scored as of 2026-09-14. Companion aggregates are computable in SQL, e.g. SELECT AVG(inside_correct_80), AVG(inside_copper_narrow) FROM {{table}}.