{"id":"W2029450559","doi":"10.1177/1550059411429528","title":"Application of Multiscale Amplitude Modulation Features and Fuzzy C-Means to Brain–Computer Interface","year":2012,"lang":"en","type":"article","venue":"Clinical EEG and Neuroscience","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Linear discriminant analysis; Brain–computer interface; Pattern recognition (psychology); Artificial intelligence; Wavelet; Cluster analysis; Discrete wavelet transform; Computer science; Electroencephalography; Discriminant; Fuzzy logic; Classifier (UML); Amplitude; Interface (matter); Wavelet transform; Speech recognition; Physics; Psychology; Neuroscience","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004986449,0.0003175282,0.0003742249,0.001065159,0.0003126954,0.0004702512,0.000402163,0.0005282706,0.000714622],"category_scores_gemma":[0.00166329,0.0001321417,0.0004320387,0.000829343,0.0002824318,0.0004876949,0.0002699209,0.0003282984,0.000167854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004145376,"about_ca_system_score_gemma":0.0004537126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004589037,"about_ca_topic_score_gemma":0.003382023,"domain_scores_codex":[0.9996462,0.00004554442,0.00003203164,0.00007931582,0.0001745456,0.00002228037],"domain_scores_gemma":[0.9996601,0.0000804456,0.00002387258,0.00002320068,0.000202076,0.00001025728],"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":[0.0002067006,0.0000806866,0.001993406,0.0002645289,0.0001166256,0.0001426506,0.0001827236,0.04410104,0.08087416,0.009953299,0.001613581,0.8604705],"study_design_scores_gemma":[0.00002464458,0.0001802054,0.005791969,0.00002883369,0.00006995559,0.0001884091,0.00003922776,0.9583214,0.02538749,0.004647041,0.00526449,0.00005639216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04689508,0.0007379165,0.94963,0.0001392394,0.0001211714,0.00009694684,0.00004814381,0.0003876794,0.00194384],"genre_scores_gemma":[0.4901562,0.0003416757,0.507865,0.00007152528,0.00009310168,0.0001236636,0.0000836267,0.00003173203,0.001233565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004589037,"threshold_uncertainty_score":0.009124696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05371333125304798,"score_gpt":0.3698321380058858,"score_spread":0.3161188067528378,"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."}}