The two open questions. The five sections before this one answer three structural questions about a column: is it orthogonal (non-redundant against the currently shipped columns, as measured by Spearman worst-cell and Chatterjee ξ — a statement about redundancy vs one specific set, not a claim of unique information content), parameterless (no per-feature tunable), and agnostic (algorithm-unambiguous). Every promoted column passed all three. Promotion has been exactly that and nothing more — the encoded rule is
promote = parameterless.PASS AND agnostic.PASS AND orthogonal.PASS
(The Gate; findings/evolution/shared_data/three_axis_gate.py:14-18, :161), and the project’s own axis audit says the quiet part out loud: it “proves consistency, not edge.” What was never asked, of any column: (1) Is the signal real? and (2) Is it useful — and to what extent?
The fresh-start rule (operator directive, 2026-07-07). This page presumes no measurement instrument. No metric, threshold, statistical test, or gate is pre-loaded here — an earlier scaffold proposed a metric checklist assembled from in-repo precedents; it was scrubbed because none of it came from dedicated research or survived an evaluation. Metrics earn their way in through one lifecycle, tracked in the two tables below:
DISCOVERED → UNDER EVALUATION → GROUNDED (or REJECTED)
Only a GROUNDED metric may write evidence into the candidate tables at the bottom of this page. Until then, every evidence cell stays NONE YET — visibly, deliberately.
Background census (context only, admits nothing): 2026-07-07-feature-realness-usefulness — the deep-research census of what machinery exists across the three repos, with provenance and telemetry. Its metric proposals are historical record, not admitted instruments.
Both tables are append-only: rows are never edited or deleted; corrections are new rows with supersedes: pointers. A metric may enter the Evaluation table only if it has a row in the Discovery table first. Every row carries a layman’s terms column so anyone can read this index and understand what is going on without knowing the mathematics. The discovery/evaluation loop updates these tables; this page is its public face.
A row means: “we found a candidate way of measuring realness or usefulness, and we verified where it comes from.” Discovery requires a resolvable primary source — an unverifiable citation is a lead, not an entry (house provenance discipline).
| Date | Metric | Aims at | In layman’s terms | Provenance (paper / implementation) | Notes |
|---|---|---|---|---|---|
| 2026-07-08 | Discovery sweep (13-agent SOTA web research + 20-instrument self-test design + adversarial hardening). All rows below are DISCOVERED only — none is admitted; each must pass the self-test battery + the shared adversarial signal-zoo before it may enter the Evaluation table. Full grounding: SOTA-GROUNDING.md · operational proof protocol: METRIC-EVALUATION-FRAMEWORK.md. Adversarial verdict: 20/20 first-draft batteries need hardening — so 0 are admissible yet. | ||||
| 2026-07-08 | Combinatorial Purged CV (CPCV) + purge/embargo | substrate / leakage-free scoreboard | Splits time so a test window never peeks at overlapping days — the honest scoreboard every other metric rides on. | López de Prado, Advances in Financial ML (2018) ch. 7,12 | feature-layer; ground FIRST; derives N_min(H) |
| 2026-07-08 | Future-perturbation invariance gate | causality (no look-ahead) | Scramble the future — the feature must not budge. If it does, it is reading tomorrow's answer. | methodology-19 §B; in-house leakage_guard.py T2 | bit-exact V(f)=0; harden: warm-state / occluded-dependency leaks |
| 2026-07-08 | Block-permutation shuffled-label null | realness (null control) | Shuffle the answers while keeping their rhythm; a real edge must collapse to chance. | Ojala & Garriga, JMLR (2010); Politis–White (2004) | block ≥ decorrelation length; publish detection envelope |
| 2026-07-08 | Effective-n deflation + BH–FDR | realness (multiple testing) | Autocorrelated data has fewer real data points than it looks; count them honestly, then correct for many tries. | Bailey–Hammersley (1946); Benjamini–Yekutieli (2001) | HAC long-run-variance N_eff (post-adversary); GARCH heavy-tail null |
| 2026-07-08 | Deflated Sharpe Ratio (on SFI paths) | realness (selection bias) | Is this just the luckiest of many coin-flips? Deflate the score by how many features were tried. | Bailey & López de Prado (2014), SSRN 2460551 | via the SFI return object; N_eff-recovery on known effective-rank |
| 2026-07-08 | Probability of Backtest Overfitting (PBO / CSCV) | realness (overfit) | If we pick the in-sample winner, does it stay a winner out-of-sample, or is it a coin-flip? | Bailey, Borwein, López de Prado, Zhu, JCF (2017), SSRN 2326253 | PBO<0.2; pair with a magnitude gate (rank-blind) |
| 2026-07-08 | Harvey–Liu–Zhu t≥3 hurdle | realness (factor-zoo) | A genuinely new signal needs a t-stat over 3, not 2 — because so many have already been tried. | Harvey, Liu & Zhu, RFS 29(1) (2016) | effective-trials denominator = frozen global universe |
| 2026-07-08 | Rank IC + ICIR + Newey-West t | usefulness (prediction) | Does the feature's ranking actually line up with next-bar returns, reliably and not by a few lucky days? | Grinold (1989); Alphalens (practitioner) | |IC|≥0.02, t≥3; blind to interaction-only (route to CMI) |
| 2026-07-08 | IC-decay / predictive half-life | usefulness (horizon) | How fast does the signal fade — smoothly (real) or in a weird spike (data-snooping)? | ml4trading / microalphas (practitioner) | selects tradable horizon; monotone-decay realness check |
| 2026-07-08 | Single-Feature Importance (SFI, OOS) | usefulness (standalone edge) | Train on this feature alone — does it beat a coin toss out-of-sample? | López de Prado, AFML (2018) §8.5 | the per-feature return object that unlocks DSR/PBO; add episodic-signal control |
| 2026-07-08 | Mean-Decrease-Accuracy + clustered MDA (ONC) | usefulness (contribution) | Scramble this feature inside a model — does accuracy drop? If not, the model wasn't using it. | López de Prado, AFML §8.4 / MLAM (2020) ch. 6 | clustered variant defeats the substitution effect |
| 2026-07-08 | Quantile monotonicity + Patton–Timmermann MR | usefulness (shape) | Do returns climb steadily across feature buckets, or only jump at the extreme ends? | Patton & Timmermann (2010); Romano–Wolf | add useful-but-non-monotone positives; route rare-veto out |
| 2026-07-08 | Conditional Mutual Information I(f;Y|S) | conditional (new info) | Given everything we already have, does this feature add NEW information about returns? | Brown, Pocock, Zhao & Luján, JMLR 13 (2012); Kraskov (2004) | rescues interaction-only; Runge local-permutation null |
| 2026-07-08 | Model-X Knockoffs / CRT / TSKI | conditional (FDR-controlled) | Make a fake twin carrying no real signal; keep the feature only if it beats its twin — with a controlled false-discovery rate. | Candès, Fan, Janson & Lv, JRSS-B 80(3) (2018) | block/TSKI variant for autocorrelated data |
| 2026-07-08 | Double/Debiased ML + CPI | conditional / causal | Strip out everything the known factors explain; is there still an effect left over? | Chernozhukov et al., Econometrics J. 21(1) (2018) | retention ≥50% of naïve; control set Z pre-registered |
| 2026-07-08 | Huberman–Kandel spanning intercept | incrementality | Is the feature's profit just repackaged momentum / volatility, or genuinely something new? | Huberman & Kandel, JF 42(4) (1987); Barillas–Shanken (2017) | HAC t(α)≥3; guard omitted-premium bias |
| 2026-07-08 | Mechanism-intensity scaling (Kyle-λ / VPIN / OFI) | economic mechanism | A real microstructure edge should get STRONGER where the mechanism is stronger — not merely correlate once. | Kyle (1985); Easley–López de Prado–O'Hara (VPIN); Cont–Kukanov–Stoikov (2014) | nonlinear-volume confound control required |
| 2026-07-08 | Per-year IC + Bai-Perron / CUSUM breaks | robustness (regime) | Is the edge steady across years, or does it live in one lucky regime and die elsewhere? | Bai & Perron (1998); Brown–Durbin–Evans (1975) | gate behind realness; block-bootstrap critical values |
| 2026-07-08 | Parameter-plateau vs needle | robustness (overfit) | Is the good setting a broad hill (robust) or a lone spike (overfit)? | Masters, Testing & Tuning Market Trading Systems (2018) | nulls regenerated from the real knob grid |
| 2026-07-08 | Detector lead-vs-coincide (event-study + MMD) | detector / rare-veto | For a rare alarm feature: does it fire BEFORE the event (useful) or just alongside it (a newspaper)? | Granger; Gretton et al. MMD (2012); Politis–Romano (1994) | for the candidate-#65 class; latent-common-cause null required |
A row means: “this discovered metric is now being evaluated on its own merits — does it actually detect what it claims, at what power, on our data?” Status moves UNDER EVALUATION → GROUNDED or REJECTED. Grounding requires empirical evidence recorded in the artifact column — never argument alone.
| Date entered | Metric | In layman’s terms | What the evaluation tests | Evidence artifact | Status |
|---|---|---|---|---|---|
| 2026-07-22 | Future-perturbation invariance gate (#1) | Scramble the future — a causal feature must not budge; a feature that peeks is caught every time. | bit-exact V(f)=0 on 870,304 real BTC@250 bars: causal FP=0 over 221M checks · planted look-ahead power=1.000 (exactly k=3 positions) · warm-state / global-stat leak FNR 1.0→0.0 with cold-reset + input-completeness (the load-bearing Harden). Real-data-only (03c / 17b deterministic corruption). | instrument_01…md · loop iter 2 | GROUNDED |
| 2026-07-22 | Combinatorial Purged CV (CPCV) + purge/embargo (#0) | The honest scoreboard: split time so a test window never shares an overlapping 3-second label with a training bar. | on 870,304 real BTC@250 bars (34.85% of consecutive bars close within 3s): naïve random k-fold leaks t=169 over 252,512 straddling overlapping-label pairs → CPCV+purge/embargo leaves 0 straddling (0 contamination); genuine signal preserved (0.55% recovery bias, power 1.0); null OOS-IC FPR 0.000; N_min(H) from real blocks. Substrate gate PASS (with #1). PBO-on-null 0.5-calibration descoped to #9 (operator ruling 2026-07-22). | instrument_00…md · loop iter 4 | GROUNDED |
| 2026-07-22 | Block-permutation shuffled-label null (#2) | Shuffle the answers in rhythm-preserving chunks; a real edge must beat the shuffles, a fake one collapses to chance. | on 870,304 real BTC@250 bars (vwap_close_deviation): null-test size 0.05 in [.037,.063] ∀L∈{25,50,100} & p-values discrete-uniform (χ² 0.41/0.75/0.80); a lazy iid shuffle would over-reject at 0.21 (block null 1.56× wider → block-permutation load-bearing); detects a real look-ahead (N_min 10k); U-shape blind FNR=1 (route to #11/#18). | instrument_02…md · loop iter 5 | GROUNDED |
| 2026-07-22 | Effective-n deflation + BH–FDR (#3) | Autocorrelated data has fewer real data points than it looks; count them honestly, then correct for many tries. | on 869,833 real BTC@250 bars (7-feature family; return kurtosis 37.7, vol-clustering 0.66): HAC effective-n = 35% of N on real data (naive would inflate significance up to 2.34× — matches SEAL); Benjamini-Yekutieli controls FDR on white/block/circular nulls (0.043/0.057/0.067 ≤ q); detects real look-ahead (N_min 3k); U-shape blind FNR=1. Findings: BY (not BH) needed for the cross-correlated family; the GARCH-specific scalar failure is muted for a rank IC. | instrument_03…md · loop iter 6 | GROUNDED |
| 2026-07-23 | Single-Feature Importance (SFI, OOS) (#6) | Train on one feature alone across 50 out-of-sample time-slices — does it beat a coin toss? | on 869,833 real BTC@250 bars over the grounded CPCV substrate: the pass-mark z* is learned from the null (2.13), not 1.0 (which would false-positive 31.5% of noise features); detects a real look-ahead (power N_min 20k); and a concentration-robust statistic rescues regime-concentrated signals the dispersion-penalizing z=mean/sd silently kills (κ_min 0.2→0.1). This is the per-feature return object that unlocks DSR/PBO (#8/#9). | instrument_06…md · loop iter 7 | GROUNDED |
| 2026-07-23 | Deflated Sharpe Ratio (on SFI paths) (#8) | Is this just the luckiest of many features? Deflate the score by how many were tried — using a pass-mark learned from shuffled data. | on 869,833 real BTC@250 bars (7-feature family): the pass-mark is the empirical best-of-family Sharpe under shuffling (not the textbook formula, which over-states 2.38× because features share the shuffled answer key). FPR 0.04 on an independent holdout; look-ahead power 0.92; pass-mark reproducible to 0.01%; ONC trial count 7 ≈ participation ratio 6 (no collapse). The permutation pass-mark closes the trial-count gaming surface by construction. Real vwap deflates to DSR 1.0. | instrument_08…md · loop iter 9 | GROUNDED |
| 2026-07-23 | Probability of Backtest Overfitting (PBO / CSCV) (#9) | If we pick the in-sample winner, does it stay a winner out-of-sample, or is it a coin-flip? | on 869,833 real BTC@250 bars (K=100 trials, 252 CSCV splits): all 7 §7 gates pass, robust across 6 seeds — exchangeable null 0.51 (chance); overfit noise fires (PBO≥0.2) in 96.7%; genuine skill PBO 0.0 (power 1.0); AUC 1.0; a clone leaves PBO unchanged (0.005); an un-purged boundary leak collapses PBO to 0, the embargo lifts it +0.44. Three real bugs fixed (verify-before-report, no threshold p-hacking): within-block IC centering, a maximally-exchangeable chance null, and the many-trials regime (K=6 was biased). Documented sensitivity: PBO is fooled by raw autocorrelation (block-perm null 0.34) → it must ride on the #0 purged folds. Paired with a round-trip-cost magnitude gate (PBO is rank-blind). | instrument_09…md · loop iter 11 | GROUNDED |
| 2026-07-23 | Harvey–Liu–Zhu t≥3 (M_eff) (#10) | Once you count everything ever tried, how big a t-stat does a feature really need to be believed? | on 869,833 real BTC@250 bars (universe M=30, Newey-West lag 30): all 6 §7 gates, robust across 5 seeds — power 1.0; the effective test count M_eff recovers a known rank of 5 exactly; a clone adds 0 (M_eff 1.0); family-wise error controlled at 0.043 vs 0.82 for a naïve OLS (≈19× worse); collapsing the universe to 1 inflates error to 0.085. Necessity (verify-before-report): the textbook analytic threshold assumes a normal null and under-controls on real heavy tails (error up to 0.130); the permutation-calibrated threshold controls it and adapts to the tail (3.19→3.58 on the worst seed). Same permutation-refinement pattern as #3 and #8. ★ completes the realness axis. | instrument_10…md · loop iter 12 | GROUNDED |
| 2026-07-23 | Rank IC + ICIR + HAC-t (#4) | Does the feature actually rank-predict the next move, and is that significant once you account for slow-drifting (autocorrelated) data? | on 869,833 real BTC@250 bars (per-period IC series, T=750, period-lag 50): all 5 §7 gates, robust across 5 seeds — a real look-ahead is detected (power 1.0 at IC=.03); the per-period IC series is long-memory (Hurst 0.81), so a naïve i.i.d. t over-states significance ≥2× (2.2–3.7) and the required sample inflates ~SE²≈5×; blind to non-monotone & interaction-only signals (FNR=1 → #19/#11/#7). First usefulness instrument. The near-white bar-level contribution meant the HAC machinery had to move to the period-IC level; the null-FPR was controlled by #10's conservative-permutation threshold (adapts to the lag-50 heavy tail → FPR 0.005). Three checkpoints of verify-before-report (injection bug, level, drift-confounded N_min). | instrument_04…md · loop iter 15 | GROUNDED |
| 2026-07-23 | IC-decay / half-life (#5) | Does the edge peak at a tradable horizon and fade smoothly (healthy) — or stay flat / spike (leakage or snooping)? | on real BTC@250 bars over horizons {1,2,3,5,8,13,20} bars (NW lag 30): all 4 §7 gates, robust across 5 seeds — a healthy signal peaks at h*=3 and decays perfectly monotonically (post-peak ρ=−1.0, half-life 10); a flat / far-horizon curve is flagged as leakage. The multi-horizon returns overlap (h≥2), so a naïve i.i.d. t family-wise-errors at 0.09–0.15 while the HAC correction controls at 0.04–0.05 — HAC is load-bearing here (unlike #4's near-white single 3s return). The heavy-tail FWER was controlled by the #10/#4 permutation family threshold (Westfall-Young max-t). Blind to non-monotone → route to #7/#19. | instrument_05…md · loop iter 16 | GROUNDED |
| 2026-07-23 | MDA + clustered-MDA (ONC) (#7) | Train a model, shuffle one feature, and see how much accuracy it costs — the importance the model actually assigns. | on real BTC@250 bars (pinned logistic base, 4 purged folds): all 5 §7 gates, robust across 5 seeds — a real look-ahead is kept (power 0.83–0.88 at IC=.03); both nulls false-positive in ≤4.2%. ONC defeats the substitution effect: a feature and its exact clone each look weak alone, but ONC co-clusters them 100% and clustered importance recovers ~1.0× the lone-driver worth. The empirical-null threshold was set conservatively (97th pctl → FPR robustly ≤.05, the #4/#5/#10 pattern). Blind to interaction-only signals (a linear model can't see them → FNR=1) → route to #11/#12/#13. | instrument_07…md · loop iter 17 | GROUNDED |
| 2026-07-23 | Quantile monotonicity + PT/RW MR (#19) | Does the mean forward return climb smoothly across feature deciles (healthy), or spike in one tail (rare-veto) — a monotone relation, not just a spread? | on real BTC@250 bars (Q=10 deciles, rank returns): all 6 gates, robust across 5 seeds — a genuinely-monotone signal is detected (power 1.0 at IC=.05); both nulls calibrate to ~.05 (∈[.03,.07]) via a per-test block-permutation p-value (the analytic normal over-rejects the autocorrelated null → not ∀H-valid). The Romano-Wolf refinement is load-bearing: a flat-then-jump rare-veto has a big spread but its low half doesn't trend → the RW test rejects it (≤1.7%) while the plain trend over-rejects (100%). Completes the usefulness axis. Monotone-only by design → measures (not requires) the miss-rate on non-monotone/interaction signals → route to #11/#12/#13. | instrument_19…md · loop iter 19 | GROUNDED |
| 2026-07-23 | Conditional Mutual Information I(f;Y|S) (#11) | Given everything we already ship, does this feature add NEW information about returns — including interaction-only signal that has zero standalone predictive power? | on real BTC@250 bars (KSG/Frenzel-Pompe k-NN CMI, Runge local-permutation null): all 8 gate-groups, robust across 2 seeds — recovers the analytic Gaussian answer (≤.01 nats); detects a genuine interaction-only signal that has ~zero marginal information (the sign-XOR archetype the marginal instruments #4/#5/#7/#19 all miss); all four nulls false-positive at 0.0. The AR(1) hardening is load-bearing: a feature's own autocorrelation, unrelated to returns, does not inflate the local-permutation test (the classic Runge anti-conservatism concern). Published blind spot: CMI grounds "new beyond the shipped set as measured" — if the conditioning set captures a hidden common cause only partially, the residual is a real conditional dependence CMI correctly reports (route imperfect-conditioning cases to #12 knockoffs / #13 DML). Opens the conditional axis. | instrument_11…md · loop iter 21 | GROUNDED |
open_deviation_bars · 15 promoted bar_close columns)All 15 are bar-close candidates: computed over the trailing 200 completed-bar closes, emitted only on bar completion, NULL through the 200-bar warm-up (schema group comment schema.sql:71-72; per-column window text column_comments.py:412-616; golden warm-up proof golden_snapshot_test.rs:823-956). Batch-5 columns were additionally rescued by the persistence fix PR #556 (computed-then-dropped before the CH INSERT, 0%-populated until 2026-06-30).
| # | Column | Card | Batch · PR · date | Three-axis evaluation + added screens (promotion basis) | Edge hypothesis | Usefulness evidence | Realness evidence |
|---|---|---|---|---|---|---|---|
| 1 | bar_petrosian_fd | — | #509 · 2026-06-03 | three-axis | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 2 | bar_katz_fd | — | #509 · 2026-06-03 | three-axis | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 3 | bar_dispersion_entropy | — | #515 · 2026-06-07 | three-axis | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 4 | bar_cecp_velocity | — | #522 impl · backfill #541 | three-axis + CECP orthogonality (#519) | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 5 | bar_categorical_recurrence_rate | 66 | batch-5 · #544 · 2026-06-27 | three-axis + worst-cell Spearman ≤0.85 + VIF≤5 | UNREGISTERED “price-level stickiness” (measurement) | NONE YET | NONE YET |
| 6 | bar_sign_markov_flux | 98 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 7 | bar_ramsey_rothman_bicov_lag1 | 113 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED time-irreversibility (measurement) | NONE YET | NONE YET |
| 8 | bar_ehlers_increment_asymmetry | 26 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 9 | bar_cox_stuart_trend_z | 23 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 10 | bar_groeneveld_meeden_b3_skewness | 99 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 11 | bar_l_kurtosis_tau4 | 2 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 12 | bar_bartels_rank_vn_ratio | 19 | batch-5 · #544 | three-axis + worst-cell | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 13 | bar_hoeffding_phi_squared_midreturn_duration | 78 | batch-6 · #568 · 2026-07-04 | three-axis + §B ξ PASS (xi_worst 0.078) | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 14 | bar_hvg_forward_visibility_horizon_mean | 59 | batch-6 · #579 · 2026-07-04 | three-axis + §B ξ PASS (xi_worst 0.175) | UNREGISTERED measurement-only | NONE YET | NONE YET |
| 15 | bar_vg_time_directed_clustering_meangap | 60 | batch-6 · #570 · 2026-07-04 | three-axis + §B ξ PASS (xi_worst 0.171) | UNREGISTERED “arrow-of-time detector” (measurement) | NONE YET | NONE YET |
| — | rogers_satchell_var_bar | 50 | batch-6 · not merged | three-axis + §B ξ PASS (promotable) — blocked on window-mean reduction ratification | NOT IMPLEMENTED — tracked here so its edge hypothesis can be registered before it ships | ||
Excluded on purpose: aggression_ratio and the other core intra-bar microstructure columns (schema.sql:29, group core) — they predate and sit outside the orthogonality-promotion campaigns. Batch-6 dashboard journal filenames say “pr569-card59”; the merged commit is #579 (2c6f7b7b) — recorded here so the discrepancy doesn’t propagate.
fxview_cache.forex_bars · 15 contributed columns)Forex kernels live in the sibling terrylica/mql5 repo (orthogonal_extension_kernels/*.rs); this dashboard carries the mirror. All evaluated orthogonal · parameterless · agnostic, entering through the same structural pipeline: parameterless-orthogonal discovery (multi-slice Spearman worst-cell screening) → Chatterjee ξ keeper-confirmation → implementation (Forex candidates hub).
DEFERRALS.md / mql5 PR #100: 3 substrate-blocked, 2 parameter-flagged). 13 = the curated live catalog: those 9 + 4 batch-3/4 first-wave columns. 15 = 13 + the two later batch-3/4 stacked-PR columns (RQW + CREx, 2026-06-24). The numbers were never the same set; this table tracks all 15 live columns.| # | Column | Family | Batch · mql5 PR | Three-axis evaluation + added screens | Edge hypothesis | Usefulness evidence | Realness evidence |
|---|---|---|---|---|---|---|---|
| 1 | anderson_darling_a2 | distributional shape | b1-2 · #91 | three-axis + Spearman worst-cell + ξ keeper | UNREGISTERED | NONE YET | NONE YET |
| 2 | edge_spread_bps | microstructure | b1-2 · #92 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 3 | hvg_clustering | visibility-graph | b1-2 · #93 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 4 | kendall_taub_ret_spread | microstructure | b1-2 · #94 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 5 | lziv_complexity_signs | sign-seq complexity | b1-2 · #95 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 6 | mann_kendall_z | trend / drift | b1-2 · #96 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 7 | sevcik_fd | fractal roughness | b1-2 · #97 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 8 | sign_two_state_entropy_rate | sign-seq complexity | b1-2 · #98 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 9 | spectral_log_slope | spectral shape | b1-2 · #99 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 10 | pomeau_irreversibility_lag1 | time-irreversibility | b3-4 · cand #25 · LOOP #109 | three-axis + worst-cell + ξ + R1–R7 re-audit | UNREGISTERED | NONE YET | NONE YET |
| 11 | hvg_degree_assortativity_coefficient | visibility-graph | b3-4 · cand #55 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 12 | hvg_mean_shortest_path_length | visibility-graph | b3-4 · cand #57 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 13 | psd_wiener_spectral_flatness | spectral shape | b3-4 · cand #72 | three-axis + worst-cell + ξ | UNREGISTERED | NONE YET | NONE YET |
| 14 | cumulative_residual_extropy | distributional info | b3-4 late · cand #38 · #126 | three-axis + worst-cell + ξ (post-catalog) | UNREGISTERED | NONE YET | NONE YET |
| 15 | right_quantile_weight_tailweight | tail asymmetry | b3-4 late · cand #7 · #127 | three-axis + worst-cell + ξ (post-catalog) | UNREGISTERED | NONE YET | NONE YET |