diff --git a/scripts/lodo-calibration.js b/scripts/lodo-calibration.js new file mode 100644 index 0000000..d11c282 --- /dev/null +++ b/scripts/lodo-calibration.js @@ -0,0 +1,193 @@ +#!/usr/bin/env node +'use strict'; + +/** + * lodo-calibration — Phases 2 and 3. + * + * The ≥40 date-cluster floor was factorGate's interval bar for a CAUSAL claim, + * mis-applied to a monotone shrink-to-observed layer. Calibration makes no causal + * claim, consumes no Bonferroni slot, and has a bounded failure mode (it can only + * over- or under-shrink). Its real risk is that the correction is DATE-DRIVEN — + * that one unusual day's offensive environment is doing all the work. + * + * Leave-one-date-out tests exactly that, and it is a harder bar than a cluster + * count: a single date whose removal reverses the improvement, or flips the + * favourite-longshot sign, fails the stat outright. + * + * ── WHAT LODO IS AND IS NOT ────────────────────────────────────────────── + * Refitting on all-but-one date uses dates that follow the held-out one, so this + * is a STABILITY test, not a point-in-time backtest. The point-in-time result is + * separate and already established (fit-past / apply-forward, CI excluding zero + * on hits / TB / RBI). Both are required; neither substitutes for the other. + * + * SUPABASE_URL=... node scripts/lodo-calibration.js + */ + +require('dotenv').config(); +const fs = require('fs'); +const path = require('path'); +const { createClient } = require('@supabase/supabase-js'); +const cal = require('../src/services/model/calibration'); +const guards = require('../src/services/model/calibrationGuards'); +const { knownNumber } = require('../src/utils/known'); + +const SB_URL = process.env.SUPABASE_URL; +const SB_KEY = process.env.SUPABASE_SERVICE_ROLE_KEY || process.env.SUPABASE_SERVICE_KEY; +const BOX = path.join(process.cwd(), '.seq-cache', 'batting-lines.json'); +const STATS = ['hits', 'total_bases', 'rbi', 'runs']; +const PAGE = 1000; +/** The favourite bucket where the over-prediction concentrates. */ +const FAVOURITE_FLOOR = 0.9; +/** Minimum rows on a held-out date for that drop to be informative. */ +const MIN_HELD_ROWS = 20; + +const FIELD = { hits: (b) => b.hits, total_bases: (b) => b.totalBases, rbi: (b) => b.rbi, runs: (b) => b.runs }; +const mean = (xs) => (xs.length ? xs.reduce((a, b) => a + b, 0) / xs.length : null); + +async function page(sb, table, select, apply) { + const out = []; + for (let from = 0; ; from += PAGE) { + const { data, error } = await apply(sb.from(table).select(select)) + .order('id', { ascending: true }).range(from, from + PAGE - 1); + if (error) throw error; + if (!data || data.length === 0) break; + out.push(...data); + if (data.length < PAGE) break; + } + return out; +} + +const isPreGame = (capturedAt, gameDate) => { + const et = new Date(new Date(capturedAt).getTime() - 4 * 3600 * 1000); + const d = et.toISOString().slice(0, 10); + return d < gameDate || (d === gameDate && et.getUTCHours() < 19); +}; + +async function main() { + const sb = createClient(SB_URL, SB_KEY, { auth: { persistSession: false } }); + const lines = JSON.parse(fs.readFileSync(BOX, 'utf8')).lines; + + const snaps = await page(sb, 'model_snapshots', + 'id, game_date, captured_at, stat, player_key, line, side, p_win, refused', + (q) => q.eq('sport', 'mlb').in('stat', STATS)); + + // Build the RAW population first so the guard has something to catch. + const raw = []; + const picked = new Map(); + for (const r of snaps) { + if (!isPreGame(r.captured_at, r.game_date)) continue; + if (r.refused || knownNumber(r.p_win) === null) continue; + const propKey = [r.game_date, r.stat, r.player_key, r.line].join('|'); + raw.push({ propKey, side: r.side, p: knownNumber(r.p_win) }); + const prev = picked.get(propKey); + if (!prev || knownNumber(r.p_win) > knownNumber(prev.p_win)) picked.set(propKey, r); + } + + // GUARD 1 — prove the raw population would have lied, then prove dedup fixes it. + const rawCheck = guards.checkPickedSideDedup(raw); + const pickedRows = [...picked.values()].map((r) => ({ + propKey: [r.game_date, r.stat, r.player_key, r.line].join('|'), + side: r.side, p: knownNumber(r.p_win), + })); + guards.assertPickedSideDedup(pickedRows); // throws if dedup failed + + const out = { + guard_1_raw_population: { violated: rawCheck.violated, mean_p: rawCheck.mean_p, both_sides_share: rawCheck.both_sides_share }, + guard_1_after_dedup: guards.checkPickedSideDedup(pickedRows), + per_stat: {}, + }; + + for (const stat of STATS) { + const rows = []; + for (const r of picked.values()) { + if (r.stat !== stat) continue; + const b = lines[`${r.game_date}|${r.player_key}`]; + const L = knownNumber(r.line); + if (!b || L === null || !r.side) continue; + const v = knownNumber(FIELD[stat](b)); + if (v === null) continue; + const over = v > L; + rows.push({ + date: r.game_date, + p: knownNumber(r.p_win), + won: (String(r.side).toLowerCase() === 'under' ? !over : over) ? 1 : 0, + }); + } + const dates = [...new Set(rows.map((r) => r.date))].sort(); + + const full = cal.fitIsotonic(rows.map((r) => ({ p: r.p, won: r.won }))); + if (!full) { + out.per_stat[stat] = { + n: rows.length, dates: dates.length, + lodo: 'NOT RUN', decision: 'REFUSE', + reason: `no isotonic map is fittable at n=${rows.length} (needs ${cal.MIN_TOTAL || 200})`, + }; + continue; + } + + // ── LEAVE ONE DATE OUT ── + const table = []; + for (const d of dates) { + const fit = rows.filter((r) => r.date !== d); + const held = rows.filter((r) => r.date === d); + if (held.length < MIN_HELD_ROWS) { + table.push({ dropped: d, held_n: held.length, verdict: 'UNINFORMATIVE', reason: 'too few rows on this date' }); + continue; + } + const map = cal.fitIsotonic(fit.map((r) => ({ p: r.p, won: r.won }))); + const applied = guards.applyOrRefuse(map, held, cal.applyIsotonic); + if (!applied.ok) { + table.push({ dropped: d, held_n: held.length, verdict: 'UNINFORMATIVE', reason: applied.reason }); + continue; + } + const ys = applied.rows.map((r) => r.won); + const bRaw = guards.safeBrier(applied.rows.map((r) => r.p), ys); + const bCal = guards.safeBrier(applied.rows.map((r) => r.pc), ys); + if (bRaw === null || bCal === null) { + table.push({ dropped: d, held_n: held.length, verdict: 'UNINFORMATIVE', reason: 'a null reached the metric' }); + continue; + } + const fav = applied.rows.filter((r) => r.p >= FAVOURITE_FLOOR); + const favBias = fav.length >= 5 ? mean(fav.map((r) => r.p)) - mean(fav.map((r) => r.won)) : null; + table.push({ + dropped: d, + held_n: held.length, + brier_delta: round4(bCal - bRaw), + improves: bCal < bRaw, + favourite_n: fav.length, + favourite_bias: favBias === null ? null : round4(favBias), + favourite_sign_holds: favBias === null ? null : favBias > 0, + verdict: bCal < bRaw ? 'holds' : 'REVERSES', + }); + } + + const informative = table.filter((t) => t.verdict !== 'UNINFORMATIVE'); + const anyReversal = informative.some((t) => t.verdict === 'REVERSES'); + const signTested = informative.filter((t) => t.favourite_sign_holds !== null); + const anySignFlip = signTested.some((t) => t.favourite_sign_holds === false); + const passes = informative.length > 0 && !anyReversal && !anySignFlip; + + out.per_stat[stat] = { + n: rows.length, + dates: dates.length, + lodo_table: table, + informative_drops: informative.length, + brier_reversals: informative.filter((t) => t.verdict === 'REVERSES').length, + favourite_sign_flips: signTested.filter((t) => t.favourite_sign_holds === false).length, + favourite_sign_untested: informative.length - signTested.length, + lodo: passes ? 'PASS' : 'FAIL', + reason: passes + ? 'improvement never reverses and the favourite over-prediction never flips sign across any single-date drop' + : (anyReversal + ? `improvement reverses when ${informative.filter((t) => t.verdict === 'REVERSES').map((t) => t.dropped).join(', ')} is dropped — the effect is date-driven` + : `the favourite over-prediction flips sign when ${signTested.filter((t) => t.favourite_sign_holds === false).map((t) => t.dropped).join(', ')} is dropped`), + }; + } + + console.log(JSON.stringify(out, null, 2)); + process.exit(0); +} + +const round4 = (v) => (v == null || !Number.isFinite(v) ? null : Math.round(v * 10000) / 10000); + +main().catch((e) => { console.error(e); process.exit(1); }); diff --git a/scripts/rebuild-tb-bands.js b/scripts/rebuild-tb-bands.js new file mode 100644 index 0000000..58f54a0 --- /dev/null +++ b/scripts/rebuild-tb-bands.js @@ -0,0 +1,121 @@ +#!/usr/bin/env node +'use strict'; + +/** + * PHASE 5 — rebuild grade bands on p_win_calibrated, for DEPLOYED stats only. + * + * total_bases is the only stat that cleared LODO, so it is the only one whose + * bands are rebuilt on calibrated values. The rest keep base-rate bands built on + * raw p_win, and the reason is named rather than left to inference. + * + * The two-bar rule still applies and still bites: TB is now CALIBRATED but no + * factor is PROVEN for it (barrel, exit velo and hard-contact-allowed were all + * THEATER), so the bands remain a base-rate read — now an honestly-numbered one. + */ + +require('dotenv').config(); +const fs = require('fs'); +const path = require('path'); +const { createClient } = require('@supabase/supabase-js'); +const cal = require('../src/services/model/calibration'); +const gb = require('../src/services/model/gradeBands'); +const guards = require('../src/services/model/calibrationGuards'); +const tl = require('../src/services/model/testLedger'); +const { knownNumber } = require('../src/utils/known'); + +const BOX = path.join(process.cwd(), '.seq-cache', 'batting-lines.json'); +const STAT = process.env.BAND_STAT || 'total_bases'; +const PAGE = 1000; + +async function page(sb, t, s, f) { + const o = []; + for (let i = 0; ; i += PAGE) { + const { data, error } = await f(sb.from(t).select(s)).order('id', { ascending: true }).range(i, i + PAGE - 1); + if (error) throw error; + if (!data.length) break; + o.push(...data); + if (data.length < PAGE) break; + } + return o; +} +const isPreGame = (c, g) => { + const et = new Date(new Date(c).getTime() - 4 * 3600 * 1000); + const d = et.toISOString().slice(0, 10); + return d < g || (d === g && et.getUTCHours() < 19); +}; +const FIELD = { hits: (b) => b.hits, total_bases: (b) => b.totalBases, rbi: (b) => b.rbi, runs: (b) => b.runs }; + +(async () => { + const sb = createClient(process.env.SUPABASE_URL, process.env.SUPABASE_SERVICE_ROLE_KEY || process.env.SUPABASE_SERVICE_KEY, { auth: { persistSession: false } }); + const lines = JSON.parse(fs.readFileSync(BOX, 'utf8')).lines; + + const snaps = await page(sb, 'model_snapshots', + 'id, game_date, captured_at, stat, player_key, line, side, p_win, refused, archetype', + (q) => q.eq('sport', 'mlb').eq('stat', STAT)); + + const picked = new Map(); + for (const r of snaps) { + if (!isPreGame(r.captured_at, r.game_date) || r.refused || knownNumber(r.p_win) === null) continue; + const k = [r.game_date, r.stat, r.player_key, r.line].join('|'); + const prev = picked.get(k); + if (!prev || knownNumber(r.p_win) > knownNumber(prev.p_win)) picked.set(k, r); + } + guards.assertPickedSideDedup([...picked.values()].map((r) => ({ + propKey: [r.game_date, r.stat, r.player_key, r.line].join('|'), side: r.side, p: knownNumber(r.p_win), + }))); + + const rows = []; + for (const r of picked.values()) { + const b = lines[`${r.game_date}|${r.player_key}`]; + const L = knownNumber(r.line); + if (!b || L === null || !r.side) continue; + const v = knownNumber(FIELD[STAT](b)); + if (v === null) continue; + const over = v > L; + rows.push({ + date: r.game_date, p: knownNumber(r.p_win), + won: (String(r.side).toLowerCase() === 'under' ? !over : over) ? 1 : 0, + archetype: String(r.archetype || 'UNLABELLED').toUpperCase(), + }); + } + rows.sort((a, b) => String(a.date).localeCompare(String(b.date))); + + // Point-in-time map, then apply forward. + const dates = [...new Set(rows.map((r) => r.date))].sort(); + const perDate = new Map(); + for (const r of rows) perDate.set(r.date, (perDate.get(r.date) || 0) + 1); + let acc = 0; let cut = dates[dates.length - 1]; + for (const d of dates) { acc += perDate.get(d); if (acc >= rows.length * 0.45) { cut = d; break; } } + const map = cal.fitIsotonic(rows.filter((r) => r.date < cut).map((r) => ({ p: r.p, won: r.won }))); + const applied = guards.applyOrRefuse(map, rows.filter((r) => r.date >= cut), cal.applyIsotonic); + if (!applied.ok) { console.log(JSON.stringify({ stat: STAT, refused: applied.reason })); process.exit(0); } + + const mc = await tl.recordAndCount(tl.supabaseStore(sb), []).catch(() => ({ cumulative_tests: 1 })); + + const byArch = new Map(); + for (const r of applied.rows) { + if (!byArch.has(r.archetype)) byArch.set(r.archetype, []); + byArch.get(r.archetype).push({ p: r.pc, won: r.won }); + } + + const out = []; + for (const [arch, rs] of [...byArch.entries()].sort((a, b) => b[1].length - a[1].length)) { + out.push(gb.buildBands(rs, { + archetype: arch, + cumulativeTests: mc.cumulative_tests, + // TB is CALIBRATED (provisional) but no factor is PROVEN for it. + proven: false, + calibrated: true, + })); + } + + console.log(JSON.stringify({ + stat: STAT, + basis: 'p_win_calibrated (PROVISIONAL)', + eval_rows: applied.rows.length, + cumulative_tests: mc.cumulative_tests, + two_bar_note: 'calibrated YES, proven NO -> bands stay a base-rate read, now honestly numbered', + bands: out, + }, null, 2)); + process.exit(0); +})().catch((e) => { console.error(e); process.exit(1); }); diff --git a/specs/lodo-provisional-calibration.md b/specs/lodo-provisional-calibration.md new file mode 100644 index 0000000..4648e56 --- /dev/null +++ b/specs/lodo-provisional-calibration.md @@ -0,0 +1,184 @@ +# LODO-gated provisional calibration — total_bases deploys, three stats refuse + +## PHASE 0 — Record correction + +**The ≥40 date-cluster deploy floor applied to CALIBRATION was the wrong +instrument, and I applied it without challenging the binding.** + +It is `factorGate`'s cluster-robust interval floor, built for a factor making a +CAUSAL claim, where the risk is a false positive dressed as mechanism. A +calibration layer is different in kind: + +- it makes **no causal claim** — it is a monotone shrink toward observed +- its failure mode is **bounded**: it can only over- or under-shrink +- it consumes **no Bonferroni slot** + +Its real risk is that the correction is **date-driven**, and leave-one-date-out +tests that directly. The replacement bar is **stricter on stability**, not looser +on standard: LODO fails a stat if removing any single day reverses the +improvement, which a cluster count cannot detect at all. + +The prior order's date premise was also wrong (05-01→08-04, "~90 dates"); the +snapshots span 07-19→08-06 = 19 dates. That was corrected in the settlement +session. The mis-bound instrument is mine. + +**The ≥40 floor is retained, correctly scoped as the PROMOTION bar** — the point +at which a stat leaves provisional status. + +--- + +## PHASE 1 — Both guards codified (11 tests) + +`src/services/model/calibrationGuards.js` + +**GUARD 1 — the both-sides tell.** Picked-side dedup is now mandatory +preprocessing, asserted. The guard fires on the CONJUNCTION of both sides being +present AND mean p_win pinned near 0.5 — either alone is unremarkable, and +flagging a genuinely balanced one-sided book would be a false alarm. + +Demonstrated on live data in this run: + +``` +raw population violated=true mean_p 0.4962 both_sides_share 0.9763 +after dedup violated=false mean_p 0.6694 +``` + +**GUARD 2 — a null that scores itself.** `safeBrier` refuses when any prediction +is null; `applyOrRefuse` drops unmappable rows rather than passing nulls +downstream. A test demonstrates the trap explicitly — `(null−1)² === 1` and +`(null−0)² === 0`, so a Brier over nulls silently equals the win rate. + +--- + +## PHASE 2 — LODO table + +Refit dropping each date; measure held-out Brier delta and the sign of the >0.9 +favourite bias. Drops with fewer than 20 held rows are marked UNINFORMATIVE +rather than counted either way. + +**A note on what LODO is:** refitting on all-but-one date uses dates that follow +the held-out one, so this is a STABILITY test, not a point-in-time backtest. The +point-in-time result is separate and already established. Both are required. + +| stat | n | dates | informative drops | reversals | sign flips | LODO | +|---|---|---|---|---|---|---| +| hits | 1,140 | 17 | 7 | **2** (07-22 n=20, 07-26 n=25) | 0 | **FAIL** | +| **total_bases** | 1,050 | 7 | 5 | 0 | 0 | **PASS** | +| rbi | 630 | 5 | 5 | **1** (08-01 n=99) | 0 | **FAIL** | +| runs | 597 | 5 | 5 | **2** (08-01 n=86, 08-05 n=244) | 0 | **FAIL** | + +### Threshold sensitivity — reported because the verdict moves + +| min held rows | hits | total_bases | rbi | runs | +|---|---|---|---|---| +| **20** (applied) | FAIL | **PASS** | FAIL | FAIL | +| 30 | PASS | **PASS** | FAIL | FAIL | +| 50 / 75 | PASS | **PASS** | FAIL | FAIL | +| 100 | PASS | **PASS** | PASS | FAIL | + +- **total_bases passes at every threshold** — the only unambiguous result. +- **runs fails at every threshold**, reversing on a 244-row date. +- **hits' failure is threshold-fragile**: it fails only when 20- and 25-row dates + are admitted, and those are the two smallest informative drops in the set. + +I chose `MIN_HELD_ROWS = 20` before seeing which stats passed, and did not move +it afterwards to preserve a deploy. The honest caveat: a per-date Brier delta on +20 rows has a standard error several times the effect being tested, so the LODO +instrument is underpowered per-drop at this sample size. That argues for +pre-registering a higher threshold — a Roundtable decision, not one to make while +holding the results. + +--- + +## PHASE 3 — Deploy decisions + +| stat | LODO | point-in-time CI | decision | +|---|---|---|---| +| **total_bases** | PASS | [−0.0061, −0.0045] | **DEPLOY-PROVISIONAL** | +| hits | FAIL | [−0.0139, −0.0097] | REFUSE — improvement reverses on 07-22 / 07-26 | +| rbi | FAIL | [−0.0092, −0.0010] | REFUSE — improvement reverses on 08-01 | +| runs | FAIL | no fittable map at the point-in-time split | REFUSE — honest null | + +Certified band for total_bases: **[0.6–0.8]**. Outside it → refuse, fall to base +rate. + +### hits was being served calibrated, and is not any more + +`snapshotService` hardcoded hits calibration since S91. hits fails LODO, so it +has been removed from the deployed set. **A stat that cannot survive dropping one +day was never calibrated — it was fitted to that day.** The consequence is real: +hits props become unstackable again for `chain.chainAcross`. That is the honest +result of measuring it, not a regression to route around, and it errs toward +withdrawing a claim rather than preserving one on a fragile verdict. + +Deployment is now driven by `CALIBRATION_DEPLOYED` (frozen, tested), not a +hardcoded stat name. + +--- + +## PHASE 4 — Auto-demotion (14 tests) + +`src/services/model/calibrationRegistry.js` + +- **Deploy needs BOTH gates** — LODO pass AND a point-in-time CI excluding zero. + Neither is waivable. +- **`reverify` demotes on the first breach**: the CI ceasing to exclude zero, or + the favourite over-prediction flipping sign (which would mean the correction is + now pushing the wrong way). The breaking date is logged. +- **Promotion to non-provisional** requires the original ≥40 date-cluster bar, + with the interval still holding. + +A provisional deploy that cannot be taken away is just a deploy; `reverify` is +what makes the label mean something. + +--- + +## PHASE 5 — Bands rebuilt on p_win_calibrated (total_bases only) + +625 eval rows on calibrated values. **The two-bar rule still bites**: TB is now +CALIBRATED but no factor is PROVEN for it (barrel, exit velo and +hard-contact-allowed were all THEATER), so bands remain a base-rate read — now an +honestly-numbered one. + +| archetype | n | base rate | bands | separation | +|---|---|---|---|---| +| UNLABELLED | 275 | 0.6255 | 1 | indistinguishable from base rate | +| BOMBER | 200 | 0.6100 | 1 | indistinguishable | +| GHOST | 87 | 0.5747 | 1 | indistinguishable | +| DRIVER | 24 | 0.7917 | 1 (PROVISIONAL) | indistinguishable | +| BRUSH | 19 | 0.4737 | 1 (PROVISIONAL) | indistinguishable | +| MIRROR | 6 | — | REFUSED | insufficient outcomes | + +Calibration compressed the served range to 0.4286–1.0. Every archetype still +collapses to a single band — calibrated p_win does not separate within archetype +any better than raw p_win did. Refused stats keep base-rate bands on raw p_win. + +--- + +## PHASE 6 — Logged, not acted on + +**The dead gradient is buried.** Over-prediction ordering on the fuller settled +set is **hits ≈ TB > runs > RBI**, not TB > RBI > runs. The skill-driven-gradient +mechanism did not survive — **RBI has the SMALLEST bias** (+0.0164). Descriptive +only; no mechanism claimed. + +**Refusal coverage.** Refused props are predictable-but-input-less rather than +genuinely uncertain (3.20 vs 3.39 AB rules out playing time). The refused set is +a MAP OF MISSING INPUTS and feeds the input-coverage roadmap. Not this order. + +**Queued candidate:** a low-parameter calibrator (Platt / beta) fits a +favourite-longshot shape on far fewer points than isotonic needs, which is +exactly the constraint that refused runs. It is a NEW estimator requiring its own +out-of-sample validation. Not built here. + +**Programme-level finding:** calibration beats every factor tried on TB / RBI / +runs, and the defect is systematic over-prediction **concentrated in favourites** +(+0.21 to +0.28 above p_win 0.9 on all four stats) rather than a uniform shift. + +--- + +## Invariants + +`p_win` never mutated — calibration rides as `p_win_calibrated` with +`calibration_status: 'provisional'`. No Bonferroni slot consumed; testLedger +factor count untouched. Counter and frozen clusters byte-identical. diff --git a/src/services/model/calibrationGuards.js b/src/services/model/calibrationGuards.js new file mode 100644 index 0000000..9af72da --- /dev/null +++ b/src/services/model/calibrationGuards.js @@ -0,0 +1,146 @@ +'use strict'; + +/** + * calibrationGuards — the two ways a calibration measurement lies to you. + * + * Both of these produced a confident, plausible, completely wrong number in the + * settlement session, and neither was visible in the output. They are codified + * here so the failure cannot recur silently. + * + * ── GUARD 1: THE BOTH-SIDES TELL ───────────────────────────────────────── + * A prop population usually carries BOTH the over and the under. Their p_wins + * sum to ~1 and their outcomes are complementary, so ANY population-level + * calibration statistic over the raw set is pinned to 0.5 by construction — not + * by the model being calibrated. + * + * Measured: the raw population read +0.0002 bias on hits ("perfectly + * calibrated"); deduped to the model-picked side it read +0.0868. Same rows, + * opposite conclusion. The tell was mean p_win sitting at 0.4998 on all four + * stats at once, which is not something a real forecaster does. + * + * So picked-side dedup is MANDATORY preprocessing, and this asserts it. + * + * ── GUARD 2: A NULL THAT SCORES ITSELF ─────────────────────────────────── + * `fitIsotonic` returns null below its minimum and `applyIsotonic` then returns + * null per row. In JavaScript `(null - 1) ** 2 === 1` and `(null - 0) ** 2 === 0`, + * so a Brier score computed over nulls silently equals the WIN RATE — a number + * in the right range, monotone in the data, and completely meaningless. It + * reported hits at 0.5567 against a 0.5684 win rate. + * + * This is the `Number(null) === 0` breach the TRUTH LAW names, wearing a metric. + * A null prediction must refuse, never score. + */ + +const { knownNumber } = require('../../utils/known'); + +/** How close to 0.5 counts as the both-sides signature. */ +const BALANCED_TOLERANCE = 0.02; + +/** + * Does this population still contain both sides of the same prop? + * + * @param {Array} rows [{ p, side, propKey }] + * @returns {object} { violated, reason, ... } — never throws, so a caller can + * decide between refusing and hard-failing. + */ +function checkPickedSideDedup(rows) { + const usable = (rows || []).filter((r) => knownNumber(r && r.p) !== null); + if (usable.length < 2) return { violated: false, reason: 'too few rows to judge', n: usable.length }; + + const sidesByProp = new Map(); + for (const r of usable) { + const k = r.propKey == null ? null : String(r.propKey); + if (k === null) continue; + if (!sidesByProp.has(k)) sidesByProp.set(k, new Set()); + if (r.side) sidesByProp.get(k).add(String(r.side).toLowerCase()); + } + let bothSides = 0; + for (const s of sidesByProp.values()) if (s.size > 1) bothSides += 1; + const propCount = sidesByProp.size; + const bothShare = propCount ? bothSides / propCount : 0; + + const meanP = usable.reduce((s, r) => s + knownNumber(r.p), 0) / usable.length; + const balanced = Math.abs(meanP - 0.5) <= BALANCED_TOLERANCE; + + // The violation is the CONJUNCTION: both sides present AND the mean pinned at + // 0.5. Either alone is unremarkable — a genuinely balanced book of one-sided + // picks is fine, and both sides present with a skewed mean means someone + // already deduped. + const violated = bothSides > 0 && balanced; + return { + violated, + n: usable.length, + props: propCount, + both_sides_props: bothSides, + both_sides_share: round4(bothShare), + mean_p: round4(meanP), + reason: violated + ? `both sides present on ${bothSides}/${propCount} props while mean p_win is ${round4(meanP)} — ` + + 'the population is balanced by construction and any calibration statistic over it is meaningless. ' + + 'Dedup to the model-picked side first.' + : null, + }; +} + +/** Same check, but refuses to continue. Use at the top of a measurement. */ +function assertPickedSideDedup(rows) { + const r = checkPickedSideDedup(rows); + if (r.violated) throw new Error(`CALIBRATION GUARD: ${r.reason}`); + return r; +} + +/** + * Brier score that refuses rather than scoring a null. + * + * @param {Array} preds + * @param {Array} outcomes + * @param {object} opts { onNull: 'throw' | 'refuse' } default 'refuse' + * @returns {number|null} null when any prediction is unreadable + */ +function safeBrier(preds, outcomes, opts = {}) { + const ps = preds || []; + const ys = outcomes || []; + if (ps.length === 0 || ps.length !== ys.length) return null; + let sum = 0; + for (let i = 0; i < ps.length; i += 1) { + const p = knownNumber(ps[i]); + const y = knownNumber(ys[i]); + if (p === null || y === null) { + // NEVER score it. (null - 1) ** 2 === 1 would pass silently. + if (opts.onNull === 'throw') { + throw new Error('CALIBRATION GUARD: a null prediction reached a Brier term'); + } + return null; + } + sum += (p - y) ** 2; + } + return sum / ps.length; +} + +/** + * Map a population through a calibration map, refusing unreadable rows rather + * than letting them through as nulls. + */ +function applyOrRefuse(map, rows, applyFn) { + if (!map) return { ok: false, reason: 'no calibration map could be fitted', rows: [] }; + const out = []; + let dropped = 0; + for (const r of rows || []) { + const pc = applyFn(map, r.p); + if (knownNumber(pc) === null) { dropped += 1; continue; } + out.push({ ...r, pc }); + } + return { + ok: out.length > 0, + rows: out, + dropped, + reason: out.length === 0 ? 'every row was unmappable' : null, + }; +} + +const round4 = (v) => (v == null || !Number.isFinite(v) ? null : Math.round(v * 10000) / 10000); + +module.exports = { + checkPickedSideDedup, assertPickedSideDedup, safeBrier, applyOrRefuse, + BALANCED_TOLERANCE, +}; diff --git a/src/services/model/calibrationRegistry.js b/src/services/model/calibrationRegistry.js new file mode 100644 index 0000000..a6e69ff --- /dev/null +++ b/src/services/model/calibrationRegistry.js @@ -0,0 +1,110 @@ +'use strict'; + +/** + * calibrationRegistry — which stats are allowed to serve a calibrated number. + * + * ── WHY THIS IS NOT THE FACTOR REGISTRY ────────────────────────────────── + * A factor makes a CAUSAL claim, so it needs a Bonferroni slot, a cluster-robust + * interval, and a bar that rises with every hypothesis the programme tests. + * Calibration makes no causal claim: it is a monotone shrink toward what was + * actually observed, its failure mode is bounded (it can only over- or + * under-shrink), and it consumes no test slot. + * + * Applying the factor gate's >=40 date-cluster interval floor to it was the + * wrong instrument. The real risk for a calibration layer is that the correction + * is DATE-DRIVEN, and leave-one-date-out tests that directly — and harder. + * + * ── TWO TIERS, AND AUTO-DEMOTION IS WHAT MAKES PROVISIONAL HONEST ──────── + * PROVISIONAL LODO passes AND the point-in-time held-out CI excludes zero. + * Serves, labelled, inside its certified band only. + * PROMOTED the original >=40 date-cluster bar, now correctly scoped as the + * PROMOTION bar rather than the deploy bar. + * + * A provisional deploy that cannot be taken away is just a deploy. `reverify` + * runs on every newly settled date and demotes on the first breach. + */ + +const { knownNumber } = require('../../utils/known'); + +const STATUS = Object.freeze({ NONE: 'none', PROVISIONAL: 'provisional', PROMOTED: 'promoted' }); +/** The ORIGINAL floor, correctly scoped: promotion, not deploy. */ +const PROMOTION_DATE_CLUSTERS = 40; + +function createRegistry(initial = {}) { + const state = new Map(Object.entries(initial)); + const log = []; + + /** Deploy requires BOTH gates. Neither can be waived. */ + function deploy(stat, evidence = {}) { + const lodo = evidence.lodo_pass === true; + const ci = Array.isArray(evidence.ci) && evidence.ci.length === 2 && evidence.ci[1] < 0; + if (!lodo || !ci) { + return { + ok: false, + status: STATUS.NONE, + reason: !lodo + ? 'LODO did not pass — the correction may be date-driven' + : 'the point-in-time held-out interval does not exclude zero', + }; + } + if (!evidence.map) return { ok: false, status: STATUS.NONE, reason: 'no calibration map supplied' }; + + state.set(stat, { + status: STATUS.PROVISIONAL, + map: evidence.map, + certified_bands: evidence.certified_bands || [], + date_clusters: knownNumber(evidence.date_clusters) ?? 0, + ci: evidence.ci, + deployed_at: evidence.at || null, + }); + log.push({ stat, event: 'deployed_provisional', at: evidence.at || null }); + return { ok: true, status: STATUS.PROVISIONAL }; + } + + /** + * Re-verify on a newly settled date. Demotes on the FIRST breach — either the + * interval ceasing to exclude zero, or the favourite over-prediction flipping + * sign (which would mean the correction is now pushing the wrong way). + */ + function reverify(stat, obs = {}) { + const cur = state.get(stat); + if (!cur || cur.status === STATUS.NONE) return { status: STATUS.NONE, changed: false }; + + const ciHolds = Array.isArray(obs.ci) && obs.ci.length === 2 && obs.ci[1] < 0; + const signHolds = obs.favourite_bias == null ? true : knownNumber(obs.favourite_bias) > 0; + + if (!ciHolds || !signHolds) { + state.set(stat, { status: STATUS.NONE, demoted_at: obs.date || null, demoted_reason: !ciHolds ? 'ci_no_longer_excludes_zero' : 'favourite_bias_flipped' }); + log.push({ stat, event: 'auto_demoted', at: obs.date || null, reason: !ciHolds ? 'ci_no_longer_excludes_zero' : 'favourite_bias_flipped' }); + return { status: STATUS.NONE, changed: true, reason: !ciHolds ? 'ci_no_longer_excludes_zero' : 'favourite_bias_flipped', breaking_date: obs.date || null }; + } + + // PROMOTION uses the original floor, now correctly scoped. + const dc = knownNumber(obs.date_clusters) ?? cur.date_clusters; + if (cur.status === STATUS.PROVISIONAL && dc >= PROMOTION_DATE_CLUSTERS) { + state.set(stat, { ...cur, status: STATUS.PROMOTED, date_clusters: dc, promoted_at: obs.date || null }); + log.push({ stat, event: 'promoted', at: obs.date || null, date_clusters: dc }); + return { status: STATUS.PROMOTED, changed: true }; + } + if (dc !== cur.date_clusters) state.set(stat, { ...cur, date_clusters: dc }); + return { status: cur.status, changed: false }; + } + + /** Is this stat allowed to serve a calibrated number for THIS p_win? */ + function serves(stat, p) { + const cur = state.get(stat); + if (!cur || cur.status === STATUS.NONE) return { serve: false, reason: 'not deployed' }; + const x = knownNumber(p); + if (x === null) return { serve: false, reason: 'no p_win' }; + const inBand = (cur.certified_bands || []).some((b) => x >= b[0] && x < b[1]); + if (!inBand) return { serve: false, reason: 'outside the certified band', status: cur.status }; + return { serve: true, status: cur.status, provisional: cur.status === STATUS.PROVISIONAL }; + } + + const get = (stat) => state.get(stat) || { status: STATUS.NONE }; + const all = () => Object.fromEntries([...state.entries()].map(([k, v]) => [k, { status: v.status, certified_bands: v.certified_bands, date_clusters: v.date_clusters }])); + + return { deploy, reverify, serves, get, all, log: () => log.slice() }; +} + +module.exports = { createRegistry, STATUS, PROMOTION_DATE_CLUSTERS }; diff --git a/src/services/snapshotService.js b/src/services/snapshotService.js index d64f483..b5564c8 100644 --- a/src/services/snapshotService.js +++ b/src/services/snapshotService.js @@ -275,6 +275,16 @@ async function loadPitcherArsenals(sport) { } catch { return out; } } +/** + * Stats whose calibration passed leave-one-date-out and may serve a calibrated + * number. PROVISIONAL: auto-demoted the first time the held-out interval stops + * excluding zero or the favourite over-prediction flips sign. + * + * hits / rbi / runs are deliberately ABSENT — each fails LODO. See + * specs/lodo-provisional-calibration.md. + */ +const CALIBRATION_DEPLOYED = Object.freeze(['total_bases']); + async function runSnapshot(sport, opts = {}) { const sp = String(sport || '').toLowerCase(); const deps = { @@ -700,37 +710,51 @@ async function runSnapshot(sport, opts = {}) { console.warn(`[challenger] ${sp} skipped:`, e.message); } - // ── FORWARD CALIBRATION (hits) ──────────────────────────────────────── + // ── FORWARD CALIBRATION (LODO-gated, per stat) ──────────────────────── // Fitted on games that are OVER, applied to tonight's props. `p_win` is NOT // touched — the counter stays byte-identical and the calibrated value rides // beside it, because a calibration map is a correction TO a forecast, not a // different forecast. // + // WHICH STATS SERVE IS MEASURED, NOT ASSUMED. The deploy bar is leave-one- + // date-out stability: refit dropping each settled date in turn, and the + // improvement must never reverse. That is the right instrument for a monotone + // shrink-to-observed layer — the factor gate's >=40 date-cluster interval + // floor was built for a CAUSAL claim and does not bind here. + // + // Measured 2026-08-07: total_bases passes at every held-size threshold. hits + // FAILS (reverses on 2026-07-22 and 2026-07-26), so it is no longer served + // calibrated even though it was — a stat that cannot survive dropping one day + // was never calibrated, it was fitted to that day. rbi and runs also fail. + // // `calibrated` is true only inside a band certified out-of-sample, and it is - // what `chain.chainAcross` requires before it will compound anything. No - // calibrator (thin history) means NOTHING is stackable — never "pass the raw - // numbers through". + // what `chain.chainAcross` requires before it will compound anything. Removing + // hits here makes hits props unstackable again, which is the honest + // consequence of the measurement rather than a regression to work around. if (sp === 'mlb') { - try { - const calSvc = deps.calibrationService || require('./model/calibrationService'); - const sbc = require('../utils/supabase').getSupabaseServiceClient(); - const calibrator = sbc ? await calSvc.fromLedger(sbc, { sport: 'mlb', stat: 'hits' }) : null; - if (calibrator) { - let marked = 0; - for (const g of enriched) { - if (String(g.stat_type || g.stat || '').toLowerCase() !== 'hits') continue; - const out = calibrator.calibrate(g.p_win); - g.p_win_calibrated = out.p_calibrated; - g.calibrated = out.calibrated; - g.calibration_reason = out.reason; - if (out.calibrated) marked += 1; + for (const stat of CALIBRATION_DEPLOYED) { + try { + const calSvc = deps.calibrationService || require('./model/calibrationService'); + const sbc = require('../utils/supabase').getSupabaseServiceClient(); + const calibrator = sbc ? await calSvc.fromLedger(sbc, { sport: 'mlb', stat }) : null; + if (calibrator) { + let marked = 0; + for (const g of enriched) { + if (String(g.stat_type || g.stat || '').toLowerCase() !== stat) continue; + const out = calibrator.calibrate(g.p_win); + g.p_win_calibrated = out.p_calibrated; + g.calibrated = out.calibrated; + g.calibration_reason = out.reason; + g.calibration_status = 'provisional'; + if (out.calibrated) marked += 1; + } + console.log(`[calibration] ${sp} ${stat} (PROVISIONAL) — ${marked} stackable; fit n=${calibrator.fit_n} through ${calibrator.fitted_through}`); + } else { + console.log(`[calibration] ${sp} ${stat} — no calibrator (thin history); nothing is stackable`); } - console.log(`[calibration] ${sp} hits — ${marked} stackable of ${enriched.filter((g) => String(g.stat_type || g.stat || '').toLowerCase() === 'hits').length}; fit n=${calibrator.fit_n} through ${calibrator.fitted_through}, bands ${JSON.stringify(calibrator.bands.map((b) => [b.lo, b.hi]))}`); - } else { - console.log(`[calibration] ${sp} — no calibrator (thin history); nothing is stackable`); + } catch (e) { + console.warn(`[calibration] ${stat} skipped:`, e.message); } - } catch (e) { - console.warn('[calibration] skipped:', e.message); } } @@ -843,5 +867,6 @@ module.exports = { generateTickerEvents, pushTickerItems, ACTIVE_SPORTS, + CALIBRATION_DEPLOYED, __internals: { propKey, gradedAtFor, indexOdds, lastName, isTopGrade, DELTA_NOISE, DELTA_MOVE, TICKER_CAP }, }; diff --git a/tests/unit/calibrationDeployGate.test.js b/tests/unit/calibrationDeployGate.test.js new file mode 100644 index 0000000..4b9273c --- /dev/null +++ b/tests/unit/calibrationDeployGate.test.js @@ -0,0 +1,30 @@ +'use strict'; + +/** + * Which stats serve a calibrated number in the live pipeline. + * + * The rule this locks: a stat that cannot survive dropping a single settled date + * was never calibrated — it was fitted to that date. hits WAS served calibrated + * and is not any more, which is the honest consequence of measuring it. + */ + +const snapshotService = require('../../src/services/snapshotService'); + +describe('the deployed set is LODO-gated', () => { + it('serves total_bases — it passed at every held-size threshold', () => { + expect(snapshotService.CALIBRATION_DEPLOYED).toContain('total_bases'); + }); + + it('does NOT serve hits, rbi or runs — each fails LODO', () => { + // hits reverses when 2026-07-22 or 2026-07-26 is dropped; rbi on 2026-08-01; + // runs on 2026-08-01 and 2026-08-05. + for (const stat of ['hits', 'rbi', 'runs']) { + expect(snapshotService.CALIBRATION_DEPLOYED).not.toContain(stat); + } + }); + + it('is frozen, so a stat cannot be added at runtime without a code change', () => { + expect(Object.isFrozen(snapshotService.CALIBRATION_DEPLOYED)).toBe(true); + expect(() => { snapshotService.CALIBRATION_DEPLOYED.push('hits'); }).toThrow(); + }); +}); diff --git a/tests/unit/calibrationGuards.test.js b/tests/unit/calibrationGuards.test.js new file mode 100644 index 0000000..da3e788 --- /dev/null +++ b/tests/unit/calibrationGuards.test.js @@ -0,0 +1,112 @@ +'use strict'; + +/** + * The two ways a calibration measurement lies. + * + * Both produced a confident, plausible, completely wrong number in the + * settlement session, and neither was visible in the output. These lock them out. + */ + +const g = require('../../src/services/model/calibrationGuards'); +const cal = require('../../src/services/model/calibration'); + +/** A population carrying BOTH sides of each prop, as the snapshot table does. */ +function bothSides(n) { + const rows = []; + for (let i = 0; i < n; i += 1) { + const p = 0.55 + (i % 7) * 0.05; + rows.push({ propKey: `prop${i}`, side: 'over', p }); + rows.push({ propKey: `prop${i}`, side: 'under', p: 1 - p }); + } + return rows; +} + +describe('GUARD 1 — the both-sides tell', () => { + it('catches the 0.4998 signature: both sides present AND mean pinned at 0.5', () => { + const rows = bothSides(200); + const r = g.checkPickedSideDedup(rows); + expect(r.violated).toBe(true); + expect(r.both_sides_share).toBe(1); + expect(Math.abs(r.mean_p - 0.5)).toBeLessThanOrEqual(g.BALANCED_TOLERANCE); + expect(r.reason).toMatch(/balanced by construction/); + }); + + it('assert form REFUSES rather than returning a number', () => { + expect(() => g.assertPickedSideDedup(bothSides(100))).toThrow(/CALIBRATION GUARD/); + }); + + it('passes once deduped to the model-picked side', () => { + // The picked side is the one the model favoured, so the mean sits well + // above 0.5 — which is what a real forecaster's book looks like. + const picked = bothSides(200).filter((r) => r.p > 0.5); + const r = g.checkPickedSideDedup(picked); + expect(r.violated).toBe(false); + expect(r.mean_p).toBeGreaterThan(0.5 + g.BALANCED_TOLERANCE); + }); + + it('does NOT fire on a genuinely balanced one-sided book', () => { + // Either condition alone is unremarkable. A book of one-sided picks that + // happens to average 0.5 is honest, and flagging it would be a false alarm. + const rows = Array.from({ length: 300 }, (_, i) => ({ + propKey: `p${i}`, side: 'over', p: i % 2 ? 0.45 : 0.55, + })); + const r = g.checkPickedSideDedup(rows); + expect(r.both_sides_props).toBe(0); + expect(r.violated).toBe(false); + }); + + it('does NOT fire when both sides are present but the mean is skewed', () => { + const rows = bothSides(50).concat( + Array.from({ length: 400 }, (_, i) => ({ propKey: `x${i}`, side: 'over', p: 0.8 }))); + const r = g.checkPickedSideDedup(rows); + expect(r.both_sides_props).toBeGreaterThan(0); + expect(r.violated).toBe(false); // already deduped elsewhere + }); +}); + +describe('GUARD 2 — a null must never score itself', () => { + it('(null-1)**2 can no longer pass as a metric', () => { + // This is the exact breach: JS scores null as 1 against a win and 0 against + // a loss, so the "Brier" silently equals the win rate. + const outcomes = [1, 1, 0, 1, 0]; + const naive = outcomes.reduce((s, y, i) => s + ((null - y) ** 2), 0) / outcomes.length; + const winRate = outcomes.reduce((a, b) => a + b, 0) / outcomes.length; + expect(naive).toBeCloseTo(winRate, 10); // the trap, demonstrated + + expect(g.safeBrier([null, null, null, null, null], outcomes)).toBeNull(); + }); + + it('refuses when ANY single prediction is null', () => { + expect(g.safeBrier([0.6, 0.4, null], [1, 0, 1])).toBeNull(); + }); + + it('can be made to hard-fail instead of refusing', () => { + expect(() => g.safeBrier([0.6, null], [1, 0], { onNull: 'throw' })) + .toThrow(/null prediction reached a Brier term/); + }); + + it('scores normally when every prediction is real', () => { + expect(g.safeBrier([1, 0], [1, 0])).toBe(0); + expect(g.safeBrier([0.5, 0.5], [1, 0])).toBeCloseTo(0.25, 10); + }); + + it('an unfittable map refuses instead of producing null predictions', () => { + // fitIsotonic returns null below its minimum; this is what must happen next. + const map = cal.fitIsotonic([{ p: 0.6, won: 1 }, { p: 0.4, won: 0 }]); + expect(map).toBeNull(); + const out = g.applyOrRefuse(map, [{ p: 0.6 }], cal.applyIsotonic); + expect(out.ok).toBe(false); + expect(out.reason).toMatch(/no calibration map/); + expect(out.rows).toEqual([]); + }); + + it('drops unmappable rows rather than passing nulls downstream', () => { + const fit = []; + for (let i = 0; i < 400; i += 1) fit.push({ p: 0.3 + (i % 60) / 100, won: i % 3 === 0 ? 1 : 0 }); + const map = cal.fitIsotonic(fit); + expect(map).not.toBeNull(); + const out = g.applyOrRefuse(map, [{ p: 0.5 }, { p: null }], cal.applyIsotonic); + expect(out.rows.length).toBe(1); + expect(out.dropped).toBe(1); + }); +}); diff --git a/tests/unit/calibrationRegistry.test.js b/tests/unit/calibrationRegistry.test.js new file mode 100644 index 0000000..a3a1ec7 --- /dev/null +++ b/tests/unit/calibrationRegistry.test.js @@ -0,0 +1,120 @@ +'use strict'; + +/** + * Which stats may serve a calibrated number. + * + * The thing these protect is the meaning of PROVISIONAL: a provisional deploy + * that cannot be taken away is just a deploy. + */ + +const { createRegistry, STATUS, PROMOTION_DATE_CLUSTERS } = require('../../src/services/model/calibrationRegistry'); + +const MAP = [{ lo: 0.5, hi: 0.7, value: 0.55, n: 300 }]; +const GOOD = { lodo_pass: true, ci: [-0.0061, -0.0045], map: MAP, certified_bands: [[0.6, 0.8]], date_clusters: 7, at: '2026-08-06' }; + +describe('deploy needs BOTH gates', () => { + it('deploys when LODO passes and the interval excludes zero', () => { + const r = createRegistry(); + expect(r.deploy('total_bases', GOOD).status).toBe(STATUS.PROVISIONAL); + }); + + it('refuses on a LODO failure however good the interval', () => { + const r = createRegistry(); + const out = r.deploy('runs', { ...GOOD, lodo_pass: false }); + expect(out.ok).toBe(false); + expect(out.reason).toMatch(/date-driven/); + }); + + it('refuses when the interval spans zero however clean the LODO', () => { + const r = createRegistry(); + const out = r.deploy('hits', { ...GOOD, ci: [-0.01, 0.002] }); + expect(out.ok).toBe(false); + expect(out.reason).toMatch(/does not exclude zero/); + }); + + it('refuses without a map — there is nothing to serve', () => { + const r = createRegistry(); + expect(r.deploy('hits', { ...GOOD, map: null }).ok).toBe(false); + }); +}); + +describe('auto-demotion is what makes provisional honest', () => { + it('demotes on the first date where the interval stops excluding zero', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + const out = r.reverify('total_bases', { ci: [-0.004, 0.001], date: '2026-08-07' }); + expect(out.status).toBe(STATUS.NONE); + expect(out.reason).toBe('ci_no_longer_excludes_zero'); + expect(out.breaking_date).toBe('2026-08-07'); + expect(r.serves('total_bases', 0.65).serve).toBe(false); + }); + + it('demotes when the favourite over-prediction flips sign', () => { + // A flip means the correction is now pushing the wrong way. + const r = createRegistry(); + r.deploy('total_bases', GOOD); + const out = r.reverify('total_bases', { ci: [-0.006, -0.004], favourite_bias: -0.03, date: '2026-08-08' }); + expect(out.status).toBe(STATUS.NONE); + expect(out.reason).toBe('favourite_bias_flipped'); + }); + + it('logs the demotion with its breaking date', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + r.reverify('total_bases', { ci: [0.001, 0.004], date: '2026-08-09' }); + const ev = r.log().find((e) => e.event === 'auto_demoted'); + expect(ev).toMatchObject({ stat: 'total_bases', at: '2026-08-09' }); + }); + + it('stays deployed while both conditions hold', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + const out = r.reverify('total_bases', { ci: [-0.007, -0.003], favourite_bias: 0.17, date: '2026-08-07' }); + expect(out.status).toBe(STATUS.PROVISIONAL); + expect(out.changed).toBe(false); + }); +}); + +describe('the >=40 date-cluster bar is the PROMOTION bar, not the deploy bar', () => { + it('does not block deployment', () => { + const r = createRegistry(); + expect(r.deploy('total_bases', { ...GOOD, date_clusters: 7 }).ok).toBe(true); + }); + + it('promotes out of provisional once it is met', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + const out = r.reverify('total_bases', { ci: [-0.006, -0.004], date_clusters: PROMOTION_DATE_CLUSTERS, date: '2026-09-15' }); + expect(out.status).toBe(STATUS.PROMOTED); + }); + + it('does not promote while the interval has stopped holding', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + const out = r.reverify('total_bases', { ci: [-0.001, 0.003], date_clusters: 60, date: '2026-09-15' }); + expect(out.status).toBe(STATUS.NONE); + }); +}); + +describe('serving is band-limited', () => { + it('serves inside the certified band and refuses outside it', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + expect(r.serves('total_bases', 0.65).serve).toBe(true); + expect(r.serves('total_bases', 0.65).provisional).toBe(true); + expect(r.serves('total_bases', 0.95).serve).toBe(false); + expect(r.serves('total_bases', 0.95).reason).toMatch(/outside the certified band/); + }); + + it('an undeployed stat never serves', () => { + const r = createRegistry(); + expect(r.serves('hits', 0.6).serve).toBe(false); + expect(r.serves('hits', 0.6).reason).toBe('not deployed'); + }); + + it('a missing p_win serves nothing', () => { + const r = createRegistry(); + r.deploy('total_bases', GOOD); + expect(r.serves('total_bases', null).serve).toBe(false); + }); +}); diff --git a/web/public/sw.js b/web/public/sw.js index 587b6f5..8cdf86e 100644 --- a/web/public/sw.js +++ b/web/public/sw.js @@ -1,2 +1,2 @@ (()=>{"use strict";let e,t,a,s,r,i={googleAnalytics:"googleAnalytics",precache:"precache-v2",prefix:"serwist",runtime:"runtime",suffix:"u">typeof 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