{"id":"W4303982406","doi":"10.3390/s22197596","title":"Classification of EEG Using Adaptive SVM Classifier with CSP and Online Recursive Independent Component Analysis","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Independent component analysis; Support vector machine; Artificial intelligence; Classifier (UML); Computer science; Component (thermodynamics); Pattern recognition (psychology); Electroencephalography; Component analysis; Machine learning; Speech recognition; Psychology; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001262927,0.00012242,0.0002309714,0.0002638384,0.0001774507,0.00002170319,0.0001573542,0.0000286301,0.0000415567],"category_scores_gemma":[0.00002494325,0.0001038722,0.00006045731,0.0006554968,0.0001521929,0.00006259743,0.0001264235,0.0002130825,9.470413e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000783973,"about_ca_system_score_gemma":0.00003112308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001010324,"about_ca_topic_score_gemma":0.00007536198,"domain_scores_codex":[0.9985319,0.0002751451,0.0002226467,0.000408675,0.0003992006,0.0001624032],"domain_scores_gemma":[0.9992676,0.0001663314,0.0002413805,0.0002138678,0.00005454652,0.00005623939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007381374,0.0007635556,0.01769305,0.00002950345,0.0004290462,0.00009246971,0.006199344,0.1542821,0.8143495,0.003330067,0.0001135103,0.001979751],"study_design_scores_gemma":[0.001089637,0.000849755,0.1703874,0.00004002662,0.0005347211,0.0001284295,0.01144153,0.7140312,0.09972904,0.0002528865,0.001014887,0.0005004867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998408,0.00002471957,0.0006520773,0.0003151893,0.00008676898,0.0001616782,0.0001061995,0.00002322666,0.000222194],"genre_scores_gemma":[0.9986587,0.000006502157,0.0009659398,0.000122959,0.00001612492,0.000003829171,0.000009997172,0.00001100733,0.0002049735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7146204,"threshold_uncertainty_score":0.4235787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06329387871427461,"score_gpt":0.288903879493987,"score_spread":0.2256100007797124,"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."}}