{"id":"W4399884112","doi":"10.3390/computers13070158","title":"Personalized Classifier Selection for EEG-Based BCIs","year":2024,"lang":"en","type":"article","venue":"Computers","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Mitacs; Holland Bloorview Kids Rehabilitation Hospital Foundation","keywords":"Classifier (UML); Brain–computer interface; Electroencephalography; Computer science; Artificial intelligence; Pattern recognition (psychology); Quadratic classifier; Machine learning; Speech recognition; Psychology","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":[0.003706948,0.001035424,0.001492008,0.002063956,0.000703897,0.001011426,0.001149741,0.0009891513,0.001256032],"category_scores_gemma":[0.01198631,0.0003126722,0.0007134771,0.001075541,0.0003570234,0.0008990184,0.0007911677,0.001303394,0.001012998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000771848,"about_ca_system_score_gemma":0.001147855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001976478,"about_ca_topic_score_gemma":0.004582463,"domain_scores_codex":[0.9974397,0.000848101,0.0001946822,0.0006550514,0.0006609614,0.0002014745],"domain_scores_gemma":[0.9949957,0.002575721,0.000356734,0.0005652952,0.001342937,0.000163498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003986808,0.0005107343,0.01213082,0.000138744,0.000218953,0.000276155,0.0002101177,0.08818381,0.01881416,0.001496055,0.007482159,0.8701395],"study_design_scores_gemma":[0.00004009358,0.0002460681,0.006240177,0.00002912014,0.00006928843,0.0001986023,0.00008055601,0.9692534,0.01611038,0.005158836,0.002534816,0.00003862717],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1175858,0.0008381681,0.8752236,0.0004126202,0.00009880942,0.0004100359,0.0003291879,0.003266687,0.001835066],"genre_scores_gemma":[0.73209,0.0002818279,0.262588,0.000264209,0.0001454672,0.0005123668,0.001580841,0.0002876873,0.00224965],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003706948,"threshold_uncertainty_score":0.01960444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04869461512978038,"score_gpt":0.3035730751520018,"score_spread":0.2548784600222214,"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."}}