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Cross-Domain Detector Meta-Analysis Report

Generated: 2026-07-16 22:44 UTC

This report is produced automatically from the committed detector-evidence aggregates under examples/real_data/*/. It normalises each detector's performance, ranks detectors within every domain, and derives a ranked backlog of refinement candidates.

Data sources

Domain Source file Schema
afdb_atrial_fibrillation early_warning_leadtime_cardiac_results.json early-warning lead-time
afdb_atrial_fibrillation_multiscale early_warning_leadtime_cardiac_multiscale_results.json early-warning lead-time
cap_kuramoto_variants cap_kuramoto_variants.json early-warning lead-time
cap_multichannel_staging cap_multichannel_aggregate.json honest-audit aggregate
chb01_seizures early_warning_leadtime_eeg_results.json early-warning lead-time
chb01_seizures_multiscale early_warning_leadtime_eeg_multiscale_results.json early-warning lead-time
csd_variant_synthetic csd_variant_synthetic_results.json early-warning lead-time
dakos_climate_transitions early_warning_leadtime_climate_results.json early-warning lead-time
dakos_climate_transitions_multiscale early_warning_leadtime_climate_multiscale_results.json early-warning lead-time
psml_grid_oscillation early_warning_leadtime_grid_results.json early-warning lead-time
psml_grid_oscillation_multiscale early_warning_leadtime_grid_multiscale_results.json early-warning lead-time
regime_adaptive_ensemble regime_adaptive_ensemble.json early-warning lead-time
sleepedf_kuramoto_variants sleepedf_kuramoto_variants.json early-warning lead-time
synthetic_honest_audit_demo synthetic_honest_audit_demo.json honest-audit aggregate

Per-domain rankings

BH-adj p is the Benjamini–Hochberg false-discovery-rate-adjusted p-value, corrected across the detectors compared on that domain, so a raw p-value that only looks significant because several detectors were tried is not read as a discovery. The raw p-value is kept beside it.

afdb_atrial_fibrillation

Rank Detector Detection rate p-value BH-adj p Beats chance
1 ensemble_weighted 33.3% 2.193e-01 4.386e-01 False
1 synchronisation 33.3% 2.193e-01 4.386e-01 False
3 critical_slowing_down 16.7% 5.627e-01 7.503e-01 False
4 transition_entropy 0.0% 1.000e+00 1.000e+00 False

afdb_atrial_fibrillation_multiscale

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down_multiscale 33.3% 2.193e-01 3.655e-01 False
1 ensemble_weighted 33.3% 2.193e-01 3.655e-01 False
1 synchronisation 33.3% 2.193e-01 3.655e-01 False
4 critical_slowing_down 16.7% 5.627e-01 7.034e-01 False
5 transition_entropy 0.0% 1.000e+00 1.000e+00 False

cap_kuramoto_variants

Rank Detector Detection rate p-value BH-adj p Beats chance
1 coherent_sustained_kuramoto 55.2% 1.112e-03 3.054e-03 True
2 normalized_delta_envelope 52.5% 1.000e-03 3.054e-03 True
3 amplitude_gated_delta_kuramoto 45.7% 1.309e-03 3.054e-03 True
4 adaptive_channel_kuramoto 20.4% 6.570e-03 1.150e-02 True
5 multi_channel_delta_kuramoto 18.4% 1.486e-02 1.883e-02 True
6 snr_weighted_delta_kuramoto 17.5% 1.614e-02 1.883e-02 True
7 sustained_delta_kuramoto 17.3% 2.320e-02 2.320e-02 True

cap_multichannel_staging

Rank Detector Detection rate p-value BH-adj p Beats chance
1 normalized_delta_envelope 52.5% 1.000e-03 3.000e-03 True
2 multi_channel_delta_kuramoto 18.4% 1.486e-02 1.614e-02 True
3 snr_weighted_delta_kuramoto 17.5% 1.614e-02 1.614e-02 True

chb01_seizures

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down 33.3% 2.155e-01 7.465e-01 False
2 ensemble_weighted 16.7% 5.582e-01 7.465e-01 False
3 synchronisation 16.7% 5.598e-01 7.465e-01 False
4 transition_entropy 0.0% 1.000e+00 1.000e+00 False

chb01_seizures_multiscale

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down_multiscale 33.3% 2.154e-01 5.387e-01 False
2 critical_slowing_down 33.3% 2.155e-01 5.387e-01 False
3 ensemble_weighted 16.7% 5.582e-01 6.998e-01 False
4 synchronisation 16.7% 5.598e-01 6.998e-01 False
5 transition_entropy 0.0% 1.000e+00 1.000e+00 False

csd_variant_synthetic

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down_multiscale 50.0% 4.055e-03 1.216e-02 True
2 critical_slowing_down_surrogate 31.2% 2.078e-02 3.116e-02 True
3 critical_slowing_down_baseline 25.0% 1.473e-01 1.473e-01 True

dakos_climate_transitions

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down 16.7% 5.144e-01 5.144e-01 False

dakos_climate_transitions_multiscale

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down_multiscale 0.0% 1.000e+00 1.000e+00 False

psml_grid_oscillation

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down 25.0% 1.953e-01 5.430e-01 False
2 transition_entropy 16.7% 4.045e-01 5.430e-01 False
3 ensemble_weighted 16.7% 4.073e-01 5.430e-01 False
4 synchronisation 0.0% 1.000e+00 1.000e+00 False

psml_grid_oscillation_multiscale

Rank Detector Detection rate p-value BH-adj p Beats chance
1 critical_slowing_down_multiscale 33.3% 7.859e-02 3.930e-01 False
2 critical_slowing_down 25.0% 1.953e-01 4.882e-01 False
3 transition_entropy 16.7% 4.045e-01 5.091e-01 False
4 ensemble_weighted 16.7% 4.073e-01 5.091e-01 False
5 synchronisation 0.0% 1.000e+00 1.000e+00 False

regime_adaptive_ensemble

Rank Detector Detection rate p-value BH-adj p Beats chance
1 normalized_delta_envelope 61.9% 6.310e-04 1.409e-03 True
2 regime_adaptive_full 61.5% 7.250e-04 1.409e-03 True
2 regime_adaptive_montage 61.5% 7.250e-04 1.409e-03 True
4 coherent_sustained_kuramoto 49.5% 6.870e-04 1.409e-03 True
5 amplitude_gated_delta_kuramoto 42.1% 7.830e-04 1.409e-03 True
6 adaptive_channel_kuramoto 16.3% 1.795e-02 2.692e-02 True
7 multi_channel_delta_kuramoto 14.7% 3.448e-02 4.145e-02 True
8 snr_weighted_delta_kuramoto 14.0% 3.684e-02 4.145e-02 True
9 sustained_delta_kuramoto 13.9% 4.926e-02 4.926e-02 True

sleepedf_kuramoto_variants

Rank Detector Detection rate p-value BH-adj p Beats chance
1 normalized_delta_envelope 99.5% 1.000e-04 2.333e-04 True
2 amplitude_gated_delta_kuramoto 27.7% 1.000e-04 2.333e-04 True
3 coherent_sustained_kuramoto 26.8% 1.000e-04 2.333e-04 True
4 adaptive_channel_kuramoto 0.0% 1.000e+00 1.000e+00 False
4 multi_channel_delta_kuramoto 0.0% 1.000e+00 1.000e+00 False
4 snr_weighted_delta_kuramoto 0.0% 1.000e+00 1.000e+00 False
4 sustained_delta_kuramoto 0.0% 1.000e+00 1.000e+00 False

synthetic_honest_audit_demo

Rank Detector Detection rate p-value BH-adj p Beats chance
1 lag1_autocorrelation 100.0% 1.000e-04 2.000e-04 True
2 window_mean_control 0.0% 1.000e+00 1.000e+00 False

Cross-domain overall ranking

Rank Detector Mean rank Domains present Wins Domain wins
1 critical_slowing_down_multiscale 1.00 5 5 afdb_atrial_fibrillation_multiscale (1), chb01_seizures_multiscale (1), csd_variant_synthetic (1), dakos_climate_transitions_multiscale (1), psml_grid_oscillation_multiscale (1)
2 lag1_autocorrelation 1.00 1 1 synthetic_honest_audit_demo (1)
3 normalized_delta_envelope 1.25 4 3 cap_multichannel_staging (1), regime_adaptive_ensemble (1), sleepedf_kuramoto_variants (1)
4 critical_slowing_down 2.00 7 3 chb01_seizures (1), dakos_climate_transitions (1), psml_grid_oscillation (1)
5 critical_slowing_down_surrogate 2.00 1 0
5 regime_adaptive_full 2.00 1 0
5 regime_adaptive_montage 2.00 1 0
5 window_mean_control 2.00 1 0
9 ensemble_weighted 2.33 6 2 afdb_atrial_fibrillation (1), afdb_atrial_fibrillation_multiscale (1)
10 coherent_sustained_kuramoto 2.67 3 1 cap_kuramoto_variants (1)
11 synchronisation 3.00 6 2 afdb_atrial_fibrillation (1), afdb_atrial_fibrillation_multiscale (1)
12 critical_slowing_down_baseline 3.00 1 0
13 amplitude_gated_delta_kuramoto 3.33 3 0
14 transition_entropy 3.83 6 0
15 multi_channel_delta_kuramoto 4.50 4 0
16 adaptive_channel_kuramoto 4.67 3 0
17 snr_weighted_delta_kuramoto 5.25 4 0
18 sustained_delta_kuramoto 6.67 3 0

Cross-domain patterns

Detectors that appear in more than one domain, sorted by mean rank:

  • critical_slowing_down_multiscale — mean rank 1.00, present in 5 domain(s), wins 5: afdb_atrial_fibrillation_multiscale (1), chb01_seizures_multiscale (1), csd_variant_synthetic (1), dakos_climate_transitions_multiscale (1), psml_grid_oscillation_multiscale (1).
  • normalized_delta_envelope — mean rank 1.25, present in 4 domain(s), wins 3: cap_kuramoto_variants (2), cap_multichannel_staging (1), regime_adaptive_ensemble (1), sleepedf_kuramoto_variants (1).
  • critical_slowing_down — mean rank 2.00, present in 7 domain(s), wins 3: afdb_atrial_fibrillation (3), afdb_atrial_fibrillation_multiscale (4), chb01_seizures (1), chb01_seizures_multiscale (2), dakos_climate_transitions (1), psml_grid_oscillation (1), psml_grid_oscillation_multiscale (2).
  • ensemble_weighted — mean rank 2.33, present in 6 domain(s), wins 2: afdb_atrial_fibrillation (1), afdb_atrial_fibrillation_multiscale (1), chb01_seizures (2), chb01_seizures_multiscale (3), psml_grid_oscillation (3), psml_grid_oscillation_multiscale (4).
  • coherent_sustained_kuramoto — mean rank 2.67, present in 3 domain(s), wins 1: cap_kuramoto_variants (1), regime_adaptive_ensemble (4), sleepedf_kuramoto_variants (3).
  • synchronisation — mean rank 3.00, present in 6 domain(s), wins 2: afdb_atrial_fibrillation (1), afdb_atrial_fibrillation_multiscale (1), chb01_seizures (3), chb01_seizures_multiscale (4), psml_grid_oscillation (4), psml_grid_oscillation_multiscale (5).
  • amplitude_gated_delta_kuramoto — mean rank 3.33, present in 3 domain(s), wins 0: cap_kuramoto_variants (3), regime_adaptive_ensemble (5), sleepedf_kuramoto_variants (2).
  • transition_entropy — mean rank 3.83, present in 6 domain(s), wins 0: afdb_atrial_fibrillation (4), afdb_atrial_fibrillation_multiscale (5), chb01_seizures (4), chb01_seizures_multiscale (5), psml_grid_oscillation (2), psml_grid_oscillation_multiscale (3).
  • multi_channel_delta_kuramoto — mean rank 4.50, present in 4 domain(s), wins 0: cap_kuramoto_variants (5), cap_multichannel_staging (2), regime_adaptive_ensemble (7), sleepedf_kuramoto_variants (4).
  • adaptive_channel_kuramoto — mean rank 4.67, present in 3 domain(s), wins 0: cap_kuramoto_variants (4), regime_adaptive_ensemble (6), sleepedf_kuramoto_variants (4).
  • snr_weighted_delta_kuramoto — mean rank 5.25, present in 4 domain(s), wins 0: cap_kuramoto_variants (6), cap_multichannel_staging (3), regime_adaptive_ensemble (8), sleepedf_kuramoto_variants (4).
  • sustained_delta_kuramoto — mean rank 6.67, present in 3 domain(s), wins 0: cap_kuramoto_variants (7), regime_adaptive_ensemble (9), sleepedf_kuramoto_variants (4).

Ranked refinement backlog

  1. Advance the critical_slowing_down_multiscale variant — it wins in 5 early-warning domain(s) (afdb_atrial_fibrillation_multiscale, chb01_seizures_multiscale, csd_variant_synthetic, dakos_climate_transitions_multiscale, psml_grid_oscillation_multiscale) and has the best mean rank (1.00) among detectors present in multiple domains. Extend it to the remaining real-data domains (EEG, cardiac) and compare it head-to-head with the baseline CSD on every corpus.
  2. Protect and productise normalized_delta_envelope for CAP sleep staging — it dominates its domain (mean rank 1.25) and should become the default reference detector there.
  3. Protect and productise lag1_autocorrelation for synthetic critical-slowing-down corpus — it dominates its domain (mean rank 1.00) and should become the default reference detector there.
  4. Deprioritise SNR-weighted Kuramoto — in the CAP multichannel panel it does not outperform the unweighted multi-channel Kuramoto detector. Reallocate effort toward channel-selection or coupling-structure variants rather than a raw SNR weighting.
  5. Audit the ensemble_weighted fusion rule — it is present in 6 early-warning domains but rarely wins (mean rank 2.33). Investigate whether the current weighting is dominated by a single indicator and whether a learned combination would help.
  6. Re-evaluate critical_slowing_down_surrogate — it appears in only one domain and never wins; consider whether the feature is under-powered or simply unsuited to that data regime.
  7. Re-evaluate regime_adaptive_full — it appears in only one domain and never wins; consider whether the feature is under-powered or simply unsuited to that data regime.
  8. Re-evaluate regime_adaptive_montage — it appears in only one domain and never wins; consider whether the feature is under-powered or simply unsuited to that data regime.
  9. Re-evaluate window_mean_control — it appears in only one domain and never wins; consider whether the feature is under-powered or simply unsuited to that data regime.
  10. Re-evaluate critical_slowing_down_baseline — it appears in only one domain and never wins; consider whether the feature is under-powered or simply unsuited to that data regime.

Notes

  • Detection rate for early-warning aggregates is approximated by observed_led / n_transitions — the fraction of transitions for which the detector produced a statistically meaningful lead.
  • A detector is marked as beating chance when its reported p-value is below 0.05; honest-audit aggregates additionally report the committed fraction_beats_chance value.
  • The CAP multichannel finding that SNR-weighted Kuramoto did not improve over the simple mean-R Kuramoto detector is carried forward explicitly; further investment in that exact spatial-R feature is not supported by the current evidence.