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"metric": "participant_mean_balanced_accuracy", "value": 0.6291666666666667, "confidence_interval_95": null, "participants": 10, "trials": 1200, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "fixed alpha100" }, { "id": "pretraining-attribution-fixed-068", "track": "pretraining-attribution-fixed", "protocol_id": "pretraining-attribution-v1", "dataset_id": "ds003810", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.5652777777777778, "confidence_interval_95": null, "participants": 10, "trials": 1200, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "fixed alpha100" }, { "id": "pretraining-attribution-selected-069", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "ds003810", "model": "labram", "metric": "participant_mean_balanced_accuracy", "value": 0.5291666666666667, "confidence_interval_95": null, "participants": 10, "trials": 1200, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-selected-070", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "ds003810", "model": "labram", "metric": "participant_mean_balanced_accuracy", "value": 0.5647222222222221, "confidence_interval_95": null, "participants": 10, "trials": 1200, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-selected-071", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "ds003810", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.6275, "confidence_interval_95": null, "participants": 10, "trials": 1200, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-selected-072", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "ds003810", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.548611111111111, "confidence_interval_95": null, "participants": 10, "trials": 1200, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-fixed-073", "track": "pretraining-attribution-fixed", "protocol_id": "pretraining-attribution-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "labram", "metric": "participant_mean_balanced_accuracy", "value": 0.6462962962962964, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "fixed alpha100" }, { "id": "pretraining-attribution-fixed-074", "track": "pretraining-attribution-fixed", "protocol_id": "pretraining-attribution-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "labram", "metric": "participant_mean_balanced_accuracy", "value": 0.5651234567901234, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "fixed alpha100" }, { "id": "pretraining-attribution-fixed-075", "track": "pretraining-attribution-fixed", "protocol_id": "pretraining-attribution-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.6231481481481481, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "fixed alpha100" }, { "id": "pretraining-attribution-fixed-076", "track": "pretraining-attribution-fixed", "protocol_id": "pretraining-attribution-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.5641975308641974, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "fixed alpha100" }, { "id": "pretraining-attribution-selected-077", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "labram", "metric": "participant_mean_balanced_accuracy", "value": 0.6444444444444444, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-selected-078", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "labram", "metric": "participant_mean_balanced_accuracy", "value": 0.5645061728395062, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-selected-079", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.6842592592592592, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "pretrained", "encoder_seed_count": 1, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "pretraining-attribution-selected-080", "track": "pretraining-attribution-selected", "protocol_id": "frozen-head-sensitivity-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "cbramod", "metric": "participant_mean_balanced_accuracy", "value": 0.6169753086419753, "confidence_interval_95": null, "participants": 36, "trials": 2160, "initialization": "constructor-random-mean", "encoder_seed_count": 3, "training_regime": "frozen_encoder_participant_disjoint_ridge", "head_selection": "inner participant validation over alpha100/10000/1" }, { "id": "fixed-classical-control-081", "track": "fixed-classical-control", "protocol_id": "pretraining-attribution-v1", "dataset_id": "ds003810", "model": "log-covariance-ridge", "metric": "participant_mean_balanced_accuracy", "value": 0.5233333333333334, "confidence_interval_95": [ 0.485, 0.5641666666666666 ], "participants": 10, "trials": 1200, "training_regime": "participant_disjoint_ridge", "fixed_covariance_shrinkage": 0.1 }, { "id": "fixed-classical-control-082", "track": "fixed-classical-control", "protocol_id": "pretraining-attribution-v1", "dataset_id": "physionet-eegmat-1.0.0", "model": "log-covariance-ridge", "metric": "participant_mean_balanced_accuracy", "value": 0.6189814814814816, "confidence_interval_95": [ 0.562037037037037, 0.6763888888888889 ], "participants": 36, "trials": 2160, "training_regime": "participant_disjoint_ridge", "fixed_covariance_shrinkage": 0.1 } ], "paired_contrasts": [ { "track": "wearable-sensor-transfer", "model": "eegnet", "comparison": "wet-source: wet->dry minus wet->wet", "participants": 102, "difference": -0.2937908496732027, "paired_participant_bootstrap_95": [ -0.3448549836601308, -0.24289011437908495 ], "unit": "absolute balanced-accuracy difference", "interpretation": "One training seed. Sensor/session order and time-on-task are confounded; not a pure causal hardware effect." }, { "track": "wearable-sensor-transfer", "model": "eegnet", "comparison": "dry-source: dry->wet minus dry->dry", "participants": 102, "difference": 0.07263071895424837, "paired_participant_bootstrap_95": [ 0.041501225490196095, 0.10392361111111113 ], "unit": "absolute balanced-accuracy difference", "interpretation": "One training seed. Sensor/session order and time-on-task are confounded; not a pure causal hardware effect." }, { "track": "wearable-etrca-calibration", "model": "ensemble-trca", "comparison": "etrca24-minus-cca-dry", "participants": 102, "difference": -0.5266884531590413, "paired_participant_bootstrap_95": [ -0.5755718954248367, -0.47671568627450983 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Prespecified single-band adaptation; not an exact three-filter-bank author reproduction. All conditions share the same future test blocks." }, { "track": "wearable-etrca-calibration", "model": "ensemble-trca", "comparison": "etrca48-minus-cca-dry", "participants": 102, "difference": -0.49959150326797386, "paired_participant_bootstrap_95": [ -0.5468409586056644, -0.4517939814814815 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Prespecified single-band adaptation; not an exact three-filter-bank author reproduction. All conditions share the same future test blocks." }, { "track": "wearable-etrca-calibration", "model": "ensemble-trca", "comparison": "etrca48-minus-etrca24-dry", "participants": 102, "difference": 0.027096949891067538, "paired_participant_bootstrap_95": [ 0.012527233115468411, 0.04193899782135077 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Prespecified single-band adaptation; not an exact three-filter-bank author reproduction. All conditions share the same future test blocks." }, { "track": "wearable-etrca-calibration", "model": "ensemble-trca", "comparison": "etrca24-minus-cca-wet", "participants": 102, "difference": -0.4135348583877996, "paired_participant_bootstrap_95": [ -0.4587418300653595, -0.3679193899782135 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Prespecified single-band adaptation; not an exact three-filter-bank author reproduction. All conditions share the same future test blocks." }, { "track": "wearable-etrca-calibration", "model": "ensemble-trca", "comparison": "etrca48-minus-cca-wet", "participants": 102, "difference": -0.17170479302832248, "paired_participant_bootstrap_95": [ -0.21868532135076257, -0.12677015250544665 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Prespecified single-band adaptation; not an exact three-filter-bank author reproduction. All conditions share the same future test blocks." }, { "track": "wearable-etrca-calibration", "model": "ensemble-trca", "comparison": "etrca48-minus-etrca24-wet", "participants": 102, "difference": 0.24183006535947713, "paired_participant_bootstrap_95": [ 0.19675585511982568, 0.28839869281045755 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Prespecified single-band adaptation; not an exact three-filter-bank author reproduction. All conditions share the same future test blocks." }, { "track": "mobile-erp", "model": "temporal-feature-logistic-regression", "modality": "scalp", "participants": 17, "comparison": "standing minus running within the same17participants", "difference": 0.27565178310202465, "paired_participant_bootstrap_95": [ 0.2265743846903483, 0.3219639440097663 ], "unit": "absolute ROC-AUC difference", "interpretation": "Secondary descriptive paired analysis; positive difference means lower AUC while running." }, { "track": "mobile-erp", "model": "temporal-feature-logistic-regression", "modality": "ear", "participants": 17, "comparison": "standing minus running within the same17participants", "difference": 0.22485304072662582, "paired_participant_bootstrap_95": [ 0.174645134376469, 0.27676874828148323 ], "unit": "absolute ROC-AUC difference", "interpretation": "Secondary descriptive paired analysis; positive difference means lower AUC while running." }, { "track": "pretraining-attribution-fixed", "model": "labram", "dataset_id": "ds003810", "participants": 10, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": -0.02416666666666667, "paired_participant_bootstrap_95": [ -0.05944444444444445, 0.010277777777777736 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-fixed", "model": "cbramod", "dataset_id": "ds003810", "participants": 10, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": 0.0638888888888889, "paired_participant_bootstrap_95": [ 0.03055555555555558, 0.09499999999999997 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-selected", "model": "labram", "dataset_id": "ds003810", "participants": 10, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": -0.03555555555555556, "paired_participant_bootstrap_95": [ -0.07000000000000002, -0.0019444444444444097 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-selected", "model": "cbramod", "dataset_id": "ds003810", "participants": 10, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": 0.07888888888888888, "paired_participant_bootstrap_95": [ 0.04527777777777778, 0.11111111111111109 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-fixed", "model": "labram", "dataset_id": "physionet-eegmat-1.0.0", "participants": 36, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": 0.08117283950617285, "paired_participant_bootstrap_95": [ 0.04969135802469138, 0.11404320987654322 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-fixed", "model": "cbramod", "dataset_id": "physionet-eegmat-1.0.0", "participants": 36, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": 0.05895061728395063, "paired_participant_bootstrap_95": [ 0.023148148148148175, 0.09567901234567901 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-selected", "model": "labram", "dataset_id": "physionet-eegmat-1.0.0", "participants": 36, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": 0.07993827160493829, "paired_participant_bootstrap_95": [ 0.04737654320987656, 0.11419753086419754 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. Not a universal model rank or proof of unseen pretraining data." }, { "track": "pretraining-attribution-selected", "model": "cbramod", "dataset_id": "physionet-eegmat-1.0.0", "participants": 36, "comparison": "pretrained minus mean of three constructor-random encoders", "difference": 0.06728395061728397, "paired_participant_bootstrap_95": [ 0.031168981481481495, 0.10432098765432099 ], "unit": "absolute balanced-accuracy difference", "interpretation": "Frozen-adapter result conditional on these splits, architecture, readout and random initializations. 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(2026), doi:10.1038/s44360-026-00096-z.", "representation": "Direct pinned PhysioNet release." }, "primary_sources": [ "https://physionet.org/content/eegmat/1.0.0/", "https://www.mdpi.com/2306-5729/4/1/14", "https://opendatacommons.org/licenses/by/1-0/" ], "publication_conditions": [ "Attribute the database and cite both the record and Zyma et al.; the license does not grant rights in individual contents or privacy rights.", "Cohort aggregates only; no participant records, EEG signals, or individual predictions." ] } ], "method_references": [ { "model": "ensemble-trca", "repository": "https://github.com/mnakanishi/TRCA-SSVEP", "commit": "35c1b8a7ebfa3774dd7266931784d04ae09f3461", "adaptation": "single fixed band;24or48target-only labels; common future test blocks5–10" } ], "interpretation_limits": { "wearable": [ "102 participants, native8channels,12targets.", "CCA/FBCCA/power are target-recording references and do not learn from source participants.", "Physical amplitude unit undocumented; scale-dependent foundation-model runs held.", "Uniform positive conversion applied to the complete training/test dataset is a different question from cross-sensor gain shift.", "In wearable-calibration, budget0 uses source-only spectral ridge and budgets12/24/48 use target-only spectral ridge: do not join these as a continuous model-update curve. In wearable-etrca-calibration, budget0 is a separate analytic CCA reference and budgets24/48 are target-only ensemble TRCA.", "Ensemble TRCA uses the same fixed6–80Hz input band, not the original three-filter-bank experiment. Its low scores do not establish the optimized method ceiling." ], "mobile_ssvep": [ "23 participants,3classes;8selected posterior scalp channels from32recorded or14ear channels, kept separate.", "Five-second and two-second protocols must not share a ranking.", "Five-second ear slow-walking CCA differs from paper by1.37percentage points; internal replay passed, exact author reproduction not established.", "Scalp/ear amplitudes checked against original headers; mislabeled IMU/EOG channels excluded." ], "mobile_erp": [ "ROC AUC is not accuracy.", "Within-participant session transfer differs from participant-disjoint SSVEP.", "Running uses17participants; standing/walking24. Compare paired common-cohort contrast separately.", "One participant has100Hz conversion vs500Hz forothers." ], "attribution": [ "Fixed-readout primary and train-only selected-readout sensitivity must both be visible; do not choose the better test score.", "Participant bootstrap is descriptive and conditional, not independent retraining uncertainty or multiplicity-adjusted inference.", "Constructor-random mean comes from3initializations, not3independent cohorts." ] }, "provenance": { "reviewed_aggregate_sha256": "fd302e0ca8d75482b8f47e3110b9a34603345a49a1a3a6664ba2e4dd975200ac", "independent_auditor_sha256": "6a2a61707c1dc5eda1a34aeb446cd50fed6441917c85cd7c1aedec30d03897bd", "review_date": "2026-09-20", "evidence_sha256": [ "352f7dd3ace055a534234af013c2d6f92ae696855c351ea33eb1ec614d583723", "472e065d8c4294fb7ce46846503b1bc2a9ccfecdebd7ff78e53ba9f6b86e6bf3", "1ab2a11ed313675672ecb091d6eaa5833ddbc48b21d5d8374b84156477aec9f8", "2a0c26e79a58ad0a9afd63e4a525557cbd9d4f563e030344b201fb6b4aabcdf2", "12afd213f5c0a37b9b643b17df4175bf5a1ba2fec9c1694db51a4971e8f0738e", "718dff16d6037cbf936f7962b31cdd0f45e0cb2f453453dae0450e5249c5ffa8", "0f73afe2ad5e2acf80794cc86b3bdc64cefcd4467990006b2651330a1d2996dd", "9bc9429a0675b77cfe92ed0c372d4530d42b6bcb110b0e0c595ea97b472b84d3", "70ba53c307b4b23ab88c49db1d8ba69263915c25d11cd195fcf5afcea59a8f3c", "1212bcfa635390840168c5809965d0bb2f5c26d446f8bcbaa1b974ec1e9a7c22", "55772d95e40cf818fedd989494de35528deddd272d974b6bd830899c00ad4502", "12d2d58a18a3ae39981c3608a8faffc574a7b4a40f0803218bea8b4384fed268", "4deea1fd9ba192bfdc8b1f4cb50b9b4687f7aeebaa3956f6a17fed9f90eec442", "ef995e7deaf7a5a185cbf3c80ba2c3d829c92c4dd32e3a993549a9f1774877f7", "e5da02b71288a4732f85735fc53b6a7650f771189d4b481ad652f1770c6ebeae", "d7a51c8b50054861ef76a410e93d2e4b7ac729f6e988582c0cfcd2d72e203a03", "bed13c46d3b280786be8e2a075d906a6e6a3bad1b43042535c400d7e2eaa47a3" ] } }