iteration 26 · 2026-07-24 · conditional axis · bounded slice 1 · laptop-drives-bigblack
The third conditional instrument: does the feature carry a forward-return effect that survives orthogonalisation against the shipped set Z? Cross-fitted DML partialling-out + a HAC standard error + the CPI predictive-impact test. All four slice-1 gates pass, robust across 2 seeds — a clean slice, because DML's orthogonalisation handles the very dependence that broke the knockoff FDR in #12.
readonly=2. 5c/5G/no-swap capped; single-thread BLAS. Reused the #12 wide slice for the conditioning set Z.| Gate (§7 row 13, slice 1) | Result (seeds 20260723 / 11) | Target | |
|---|---|---|---|
| Gaussian coverage & null t~N(0,1) | coverage 0.94 · null-t mean 0.18 std 0.91 · FP 0.05 / 0.03 | coverage ∈[.93,.97] & FP≤.05 | PASS |
| Admit (R≥.5, HAC t≥3, CPI p<.05) | power 0.967, R 1.05, HAC-t 6.0, CPI-p 0.003 | power ≥ .8 | PASS |
| Null FP (block-perm target) | 0.067, null-t std 0.93 | ≤ .06 | PASS |
| Retention calibration | indep 1.22 (admit) · Z-explained 0.24 (reject) | R_hi>.5 & R_lo<.5 | PASS |
Coverage / calibration. On a jointly-Gaussian construction with a known partial effect θ* (Y=Z·w_Y+e_Y, f=Z·w_f+θ·e_Y+e_f → exact partial slope θ/(θ²+1)), the cross-fitted DML confidence interval covers θ* in 94% of reps and under θ*=0 false-positives at 5% — the estimator is calibrated. (The null-t mean 0.18 is a mild bias from cross-fitting on autocorrelated Z; coverage + FP are the operative calibration and both pass.)
Retention separates conditional-real from Z-redundant. A feature whose signal is mostly Z-independent retains R≈1.2 (admit); a feature whose signal is mostly Z-explained — genuinely sharing Z's contribution to a Z-dependent Y — collapses to R≈0.24 (reject). The R=.5 threshold cleanly separates a feature that adds forward information from one redundant with the shipped set.