What happened in this iteration, in plain words: the counting instrument went for its final certification โ and produced the campaign's most interesting result yet. Test one (does adding its score improve the certified panel's forecasts?): no โ improvement statistically indistinguishable from zero. Test two (do features it rates "regime-stable" actually keep their orthogonal status?): here came the surprise. The relationship is strong, statistically decisiveโฆ and backwards. Features whose behavior is most stable across regimes are the ones most likely to LOSE their orthogonal status. Once you see why, it's obvious: the instrument measures how stably a feature is coupled to the market's core signals โ and a stably-coupled feature is stably predictable from those signals, which is the definition of NOT orthogonal. The market's activity dial (volumes, trade counts) is stably coupled โ and stably redundant. The engineered features that stay orthogonal do so precisely because their coupling keeps breaking. So: the instrument is honest (its detector demonstrably works), but it answers a different question than the statuses ask. Per the rulebook: gate role rejected, the naive mapping question is formally KILLED, the inverted discovery goes on the books, and the successor asks the semantically exact question โ count the per-regime orthogonality verdicts themselves.
Preflight (A0)
2026-07-03 12:19 UTC โ load1 3.49 / 32 cores (โค24) ยท no competing nasimubd jobs ยท 21 GiB available, si/soโ0 ยท clickhouse-server active ยท sidecar active + /health healthy โ ALL PASS. One capped run (0.66 min), readonly=2, pre-authorized (03b), zero generated values (03c). Leakage safety: expanding-window k (envs 0..t only per transition โ same information timing as the admitted gauges; iteration 8's static k would have leaked future regimes).
The two legs and what they showed
M4 โ incremental value (sealed C2'/C3' machinery, apply-once temporal split):
baseline (admitted panel) conditional AUC 0.9753
+ expanding k_frac conditional AUC 0.9802
ฮAUC +0.0049, 95% CI [โ0.0033, +0.0145] โ contains 0 โ NO admissible lift
collinearity vs admitted: max|ฯ| = 0.32 (partially overlaps redundancy โ
consistent with the mechanism below)
โ as a PANEL GAUGE: EXCLUDE(DEAD-WEIGHT)
M5' โ real-data power against the persistence label (pre-registered: ฯ > 0):
ฯ(k_frac, stays-orthogonal) on held-out among-orth rows (n=256):
ฯ = โ0.291 95% CI [โ0.356, โ0.198] pairing-null band [โ0.12, +0.12]
โ the detector WORKS (signal far outside the null band = power demonstrated)
โ but the direction is INVERTED vs the pre-registered mapping โ leg FAILS
(apply-once: recorded at the pre-registered criterion, no re-tuning)
WHY INVERTED (mechanism, recorded as discovery โ LEDGER row 14):
k measures stability of the anchorsโfeature RELATIONSHIP.
stably anchored โ stably PREDICTABLE from the core set โ NOT orthogonal.
k=9 activity/size family: stably coupled โ flips back to redundant.
curated bar_* features: orthogonal BECAUSE their coupling keeps breaking (kโค2)
โ regression invariance and status stability are DIFFERENT AXES.
The statuses need per-regime ORTHOGONALITY-VERDICT counting.
Verdicts (frozen grammar)
Object
Verdict
Where
Permutation k-of-N as a panel gauge / status-boundary gate
EXCLUDE(DEAD-WEIGHT) โ ฮAUC CI โ 0; M5โฒ pre-registered direction failed
KILLED-QUESTION โ it measures anchor-coupling stability, which anti-predicts persistence (ฯ=โ0.291, decisive)
LEDGER row 14
The inverted signal ("stable coupling โ persistent non-orthogonality")
First-class discovery on the books; may re-enter the ladder as a NON-orthogonality predictor candidate
LEDGER row 14 ยท BONEYARD revisit path (b)
The k measurement + its calibration design (own-permutation null)
Retained report-only; the calibration pattern carries to successors
row 11 measurement clause stands
Technical record
Item
Value
Leakage safety
expanding-window k_frac = k(envs 0..t)/(t+1) per transition epoch t (epochs 0โ1 unavailable โ cal-median impute); P=500 per expanding run (DERIVED, cost)
Machinery
M4 via the seal-validated m4_run (cluster bootstrap B=400, refit pairing-null); M5โฒ = parameterless Spearman with cluster bootstrap + pairing-null (no thresholds, no new knobs)
Panel
sha-pinned tierA_v3 cells; cal 547 / test 256 among-orth; 100% of test rows carried a k value
Numbers
M4 ฮAUC +0.0049 CI [โ0.0033,+0.0145] ยท max|ฯ| 0.32 ยท M5โฒ ฯ โ0.291 CI [โ0.356,โ0.198] vs null ยฑ0.12 ยท wall 0.66 min
one 0.66-min capped run ยท 10 readonly=2 SELECTs ยท zero writes outside audit folder + dashboard
โถ Next iteration
Iteration 10 = Frontier #2, refined successor: verdict-stability k-of-N โ count the thing the statuses are actually about. In plain words: instead of asking "is the feature's coupling to the core signals stable per regime?" (iteration 9 proved that's the wrong axis โ it anti-predicts), ask the literal status question per regime: "was this feature ORTHOGONAL in regime e, yes or no?" โ then k = in how many of the 10 regimes the orthogonality verdict held. A feature orthogonal in 9 of 10 regimes is CONDITIONAL material by definition; orthogonal in 2 is FRAGILE. Technically: per-env redundancy verdict (the admitted G0 machinery, worst-cell convention) counted across the 10 environments, with the same own-permutation calibration pattern that survived iteration 8, driven through the ladder (M0โM5โฒ) in one bounded slice โ including the M5โฒ direction test against the persistence label, which for THIS variant has a committed-anchored positive expectation (per-regime orthogonality is literally the label's own ingredient at t). Steering alternatives: full forex grid (fix-plan step 6), forex k-of-N, or F014 (identifiability-sharpened).
Iteration 9 ยท 2026-07-03 ยท Frontier #2 admission legs: gate excluded, question killed, inverted discovery recorded ยท capped read-only ยท zero synthetic data ยท append-only