Codex Reset Forecast Model & Backtest

The peak uses the latest 16 non-observation reset records, comparing three-hour windows at each UTC hour and converting the result to your timezone. Ties use the earliest UTC start. Historical percentiles use the latest 16 completed gaps, retaining only gaps longer than the current wait, then linearly interpolating P25/P50/P75 of the remaining time. P50 is the median comparable historical wait, not an announced next reset. When data is stale, percentile dates stay anchored to the displayed data timestamp.

We use a Gamma–Poisson model with prior α=1 and β=72 hours. n is the number of completed intervals, T their total hours, and w the current wait covered by the saved data.

Current n=16，α=17，β=1895.55h. The 24- and 48-hour probabilities are calculated separately from the formula, without compounding rounded percentages.

Model intervals use the 5th–95th percentiles of the posterior arrival rate. They capture only uncertainty within the model, excluding missing records, policy changes and account rollout delays.

Starting with 8 completed intervals, each forecast uses only earlier history. While still waiting, checkpoints at 0, 24, 48 and 72 hours predict the next 24/48 hours. Lower Brier is better. Checkpoints within a gap are correlated, not independent samples or an accuracy percentage.

Parameters are fixed in advance; this backtest reports limitations rather than selecting the best-looking window. Announcements are not continuous account monitoring. Coverage and scope remain uncertain, so confidence stays low. Clear announcements take priority, and your account reset remains governed by /status.