{"id":"W1989492719","doi":"10.1016/j.neuroimage.2007.01.016","title":"Groupwise independent component decomposition of EEG data and partial least square analysis","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research; James S. McDonnell Foundation","keywords":"Independent component analysis; Principal component analysis; Dimensionality reduction; Pattern recognition (psychology); Partial least squares regression; Computer science; Curse of dimensionality; Artificial intelligence; Redundancy (engineering); Component analysis; Electroencephalography; Exploratory data analysis; Data mining; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006874911,0.0009531616,0.0006579317,0.0009790494,0.0002859666,0.0006749138,0.0005110009,0.0006111096,0.005341568],"category_scores_gemma":[0.004129175,0.0003192127,0.0008865027,0.00197382,0.0005196376,0.0007179429,0.0005312208,0.00124204,0.002076827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609707,"about_ca_system_score_gemma":0.0006909908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001391318,"about_ca_topic_score_gemma":0.001498098,"domain_scores_codex":[0.9994318,0.0002111829,0.00002902266,0.0001137666,0.0001669015,0.00004726702],"domain_scores_gemma":[0.9991956,0.0003731966,0.00006118336,0.0001799542,0.0001693115,0.00002072907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002813469,0.0001417791,0.0008081741,0.0004861104,0.0002373962,0.0002067379,0.0002177685,0.04786054,0.07140392,0.04386814,0.01141502,0.8230731],"study_design_scores_gemma":[0.00005423948,0.0002920778,0.01037553,0.00007998337,0.000202891,0.0007186116,0.0002124816,0.7988391,0.04873187,0.1071699,0.03321521,0.0001080625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004735276,0.0003639812,0.9929423,0.0001262074,0.00008829634,0.00004973214,0.0002025899,0.0003904159,0.001101145],"genre_scores_gemma":[0.1002432,0.001211026,0.891118,0.0001012065,0.0002194418,0.0003886818,0.0009960056,0.0005349033,0.005187529],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005341568,"threshold_uncertainty_score":0.01786929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04626839168322982,"score_gpt":0.3235410880467755,"score_spread":0.2772726963635457,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}