{"id":"W2169765232","doi":"10.1109/iembs.2008.4649361","title":"Real-time automated neural-network sleep classifier using single channel EEG recording for detection of narcolepsy episodes","year":2008,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; London Health Sciences Centre; University of Waterloo","funders":"","keywords":"Computer science; Electroencephalography; Narcolepsy; Artificial intelligence; Artificial neural network; Sleep Stages; Classifier (UML); Sleep (system call); Pattern recognition (psychology); Speech recognition; Polysomnography; Neuroscience; Psychology; Neurology","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":[0.0001886095,0.0001958172,0.000292924,0.000127654,0.0003738066,0.00004274801,0.0002227536,0.0001072975,0.00002889411],"category_scores_gemma":[0.0001282349,0.0001746665,0.0001283551,0.0004218902,0.0001263362,0.0003058069,0.00007918597,0.00009692871,0.000010188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005958934,"about_ca_system_score_gemma":0.00001782418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001010124,"about_ca_topic_score_gemma":0.00001023034,"domain_scores_codex":[0.9983795,0.0001284925,0.0004058887,0.0004576958,0.0001849831,0.0004434915],"domain_scores_gemma":[0.9989858,0.0004119147,0.0002219035,0.0002245299,0.00008131481,0.00007459203],"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":[0.00006587538,0.00006618271,0.00007170468,0.00002540502,0.0000076168,0.000006055387,0.0001613524,0.01107692,0.9856623,0.00001745309,0.0007943546,0.002044727],"study_design_scores_gemma":[0.0001875312,0.0001958272,0.0001384493,0.00003127698,0.000006701503,0.00006518597,0.00001460198,0.5521587,0.4468958,0.0001076746,0.00007826057,0.0001199901],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812474,0.00001446962,0.01545695,0.0001027595,0.0008057388,0.0003803308,0.000006544688,0.0009184056,0.001067447],"genre_scores_gemma":[0.9916622,0.00001112837,0.007269333,0.0001481914,0.0001875414,0.00001408328,0.000001429185,0.00003520965,0.0006708829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5410817,"threshold_uncertainty_score":0.7122692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06425433492076416,"score_gpt":0.2824641996661011,"score_spread":0.2182098647453369,"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."}}