{"id":"W4214728093","doi":"10.1016/j.bspc.2022.103539","title":"Sleep staging using semi-unsupervised clustering of EEG: Application to REM sleep behavior disorder","year":2022,"lang":"en","type":"article","venue":"Biomedical Signal Processing and Control","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Electroencephalography; Sleep Stages; Sleep (system call); Cluster analysis; Computer science; Discriminative model; Artificial intelligence; Pattern recognition (psychology); Slow-wave sleep; Polysomnography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003277636,0.0001599016,0.0002554583,0.0001465495,0.0004766361,0.000083699,0.0003062851,0.00004825663,0.0000637499],"category_scores_gemma":[0.00003999879,0.0001444999,0.00004801028,0.0004149848,0.000141053,0.0001239249,0.0002177481,0.0002125788,0.000001413648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004563899,"about_ca_system_score_gemma":0.00004098818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004697016,"about_ca_topic_score_gemma":0.000001291486,"domain_scores_codex":[0.9981791,0.0001252516,0.0003660708,0.0004874037,0.0005253501,0.0003168212],"domain_scores_gemma":[0.9993858,0.0001284656,0.0001381431,0.0001299915,0.00003894044,0.0001786675],"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":[0.00007578895,0.0001280101,0.0007098213,0.00006041977,0.000003899954,0.000006599189,0.0004510918,0.001547893,0.6683172,0.000006913798,0.000005939076,0.3286864],"study_design_scores_gemma":[0.001252592,0.0002795185,0.0009109318,0.00005535875,0.00004613406,0.00003739499,0.0003797903,0.9792699,0.0155472,0.00004935922,0.001932243,0.0002395464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5486331,0.0001920088,0.4502715,0.0004345177,0.00007653412,0.0002763102,0.00002868335,0.00005925392,0.00002805779],"genre_scores_gemma":[0.9981949,0.000001226407,0.0006246981,0.0009489489,0.00008437563,0.0001002777,0.000003176782,0.00002008908,0.00002226415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.977722,"threshold_uncertainty_score":0.5892536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01625624195287406,"score_gpt":0.267794249238445,"score_spread":0.251538007285571,"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."}}