Seven orders of measurement-first repair. The served grade does not move.
A0/A1 — the unordered page walk returned the right COUNT and the wrong ROWS:
410-617 of 2,490 duplicated with an equal number never returned, while
rows.length matched the server exactly. safePaginate orders on a real unique
key, verifies the tuple at runtime, and THROWS on a query error instead of
treating it as end-of-data. Both hits PROVES are withdrawn: they were drawn
through that reader, and defense_by_direction's distinct-n was likely below
the gate floor all along.
A2/A2b — rolled across every reader: 11 FAIL -> 0. Composite keys pulled from
pg_index (the context tables are dated-composite and had no single unique
column). The unordered helper is deleted, not parked.
A3 — ledgerService and retentionService defaulted the SAME env var to
DIFFERENT versions, so no ledger row ever carried the marker eligibility
requires. One source now. model_snapshots settlement moved onto the cron:
15,484 -> 28,894 settled, repaired-champion 0 -> 7,556.
A4 — hitsFactorContext takes an as-of cutoff. Refusal over reconstruction: no
row at-or-before the date means the factor does not apply, never the nearest
row. Live path unchanged, proven 400/400 on real rows.
A5 — factor_inputs freezes what the factor READ, never the multiplier, so an
audit can recompute and check. It also recorded the finding: the three hits
factors have NEVER fired. prop.opponent and prop.opposing_pitcher are read by
the resolver and written by nothing.
A6/A7 — matchupKeys resolves those keys from the posted lineup plus the
schedule's probable pitchers, and fires the factors into a SHADOW freeze:
248 fires on 308 props, 245 of which would move the grade. The served
forecast is untouched. specs/a8-shadow-factor-gate.md pre-registers the test
that decides whether they ever go live.
Nothing is turned on. CALIBRATION_DEPLOYED stays []. Both verdicts stay
withdrawn. 4,772 tests / 371 suites green, web build exit 0, read-integrity
harness 34/34.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
PREMISE CORRECTION FIRST. statModel.js and correlateValidator.js do not exist
in this repository. The validation spec's only prior form is
src/services/python/blueprints/unconventional.py -- a Flask blueprint in the
Python service that is offline in production, scoring NBA factors against a
warehouse that was never populated -- and tests/unit/supplementSystems.test.js
requires only fs and path while defining its own validateFactor inline at line
368. Those tests assert a re-implementation of the thresholds, not an
implementation, which is exactly why they passed for months while nothing was
connected. The diagnosis behind the order is right -- every challenger was
measured without a gate -- but the cause is that there was no gate on the Node
side to import. So it is built, to the exact spec.
correlateValidator: n>=500, |r|>=0.15, p<0.05, Bonferroni across the sweep.
The p-value is exact rather than approximated (t-transform through a
regularized incomplete beta) and is verified in the suite against known
values, because scipy is not available here. Pairs with an unknown side are
dropped, never zero-filled -- a zero-fill inside a correlation does not add
noise, it invents a point at the origin.
THE RUN, hits, n=570, Bonferroni-8: every skill feature fails, and not
narrowly. The strongest marginal correlation against the counter's residual is
0.062 against a 0.15 bar. That is an effect-size failure at a sample that
would have found a real effect comfortably -- a clean, well-powered negative.
The head-to-head agrees: value engine 0.0499 against the counter's 0.166,
delta -0.116 with CI [-0.189, -0.043]. Not promoted.
THE RUN, total bases, n=295: cannot be tested, and that is the finding.
hard_hit_pct shows a marginal r of 0.153 -- above the threshold -- and exit
velo 0.124, refused solely because n is 205 short of 500. It is the most
encouraging number this work has produced, and it is what the physics
predicts: contact quality governs extra bases, not whether a grounder finds a
hole. We have been testing skill inputs on the one stat where they should not
matter much.
Two things the run forced. Feature verdicts are now PER STAT, because marking
these DEAD sport-wide on hits evidence would have killed, for total bases, the
features that look most alive there -- per-sport doctrine one level deeper.
And the gate now reports r and p even when underpowered, because "not enough
data yet" and "nothing here" demand opposite decisions and a bare refusal was
hiding the best signal on the board.
Next: build the compound TB projection (skillProjection still refuses total
bases by design, since a deterministic bases-per-hit made P(TB>=2) identical
to P(hits>=1)), accrue to n>=500, re-run this gate. Leave hits alone.
4,200 tests green (334 suites); web build exit 0; counter byte-identical.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9
builtbykev