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Per-reason drop counts ship as excluded_hours.","That exclusion protects the truth side only. Our forecast anchors on the last hour carrying a positive D, so where that hour is one of the same placeholders, the anchor seeding our forecast is the BA's own day-ahead value \u2014 the hour we score is dropped, the hour that seeded it is not. placeholder_pct reports how often the BA's readings arrive that way. The effect correlates our error with the operator's rather than shrinking it; see the methodology's limits.","The official arm is scored twice: as-issued (the earliest day-ahead forecast we observed, the fair comparison) and as-revised (EIA's current value, which for a revising BA carries hindsight). Both verdicts are published.","Verdicts are decided on mean MAPE. median_ape, mae and wape are published for interpretation and decide nothing.","Leads are nominal unless lead_basis is 'observed'. Our realized lead is shorter than its label, and the 24h arm is NOT lead-matched against the operators' documented 17-41h submission window \u2014 see the methodology's limits before quoting a lead.","Excluded BAs are published with their reason rather than omitted.","Hours first seen more than a few hours after they passed are excluded (stale_capture): their earliest-observed forecast is a post-revision value, so scoring it as 'as-issued' would collapse the distinction the dual official arm exists to draw. Where any were excluded, stale_capture_impact reports how their removal moved both arms.","Rows carry serve_grade \u2014 our own rolling grade for the exact series scored, at the same horizon. A row graded 'rollback' is one we already know is failing, and it is marked rather than presented as an ordinary comparison.","This arm always scores the model, so where serves_scored_model is false the row measures the forecaster rather than the series a user of that BA is served \u2014 see served_series."],"regions":[{"absent_hours_bias_pct":null,"df_asissued_coverage":0.9082,"df_coverage":0.9986,"df_last_published_at":"2026-09-10T05:00:00Z","df_longest_gap_end":"2026-09-10T06:00:00Z","df_longest_gap_hours":1.0,"df_stale_hours":1.0,"leads":{"24h":{"delta_mape":0.443,"delta_mape_vs_revised":-0.107,"delta_median_ape":0.715,"delta_wape":0.635,"excluded_hours":{"first_seen_placeholder":12,"no_df":1,"no_gridpulse":7,"stale_capture":65,"unresolved_stub":3,"unsettled":0},"gridpulse":{"mae":105.6,"mape":3.403,"median_ape":2.813,"n":631,"wape":3.298},"lead_basis":"observed","n":631,"observed_lead_h":23.89,"official":{"mae":125.9,"mape":3.846,"median_ape":3.528,"n":631,"wape":3.933},"official_revised":{"mae":105.1,"mape":3.296,"median_ape":2.895,"n":631,"wape":3.285},"scoreable":true,"serve_grade":{"acceptable_max":7.0,"grade":"target","horizon":"24h","model":"ensemble","n_7d":167,"rolling_mape_7d":2.737338239336951},"stale_capture_impact":{"gridpulse_mape_shift_pts":0.084,"n_hours_excluded":65,"note":"same hours rescored without the stale-capture filter; 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