{"id":"W4280523107","doi":"10.1088/1361-6579/ac8ccd","title":"Machine learning to support triage of children at risk for epileptic seizures in the pediatric intensive care unit","year":2022,"lang":"en","type":"article","venue":"Physiological Measurement","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; St. Michael's Hospital; University of Calgary; University of Toronto","funders":"","keywords":"Triage; Medicine; Receiver operating characteristic; Intensive care unit; Pediatric intensive care unit; Early warning score; Intensive care medicine; Intensive care; Emergency medicine; Emergency department; Medical emergency; Pediatrics; Internal medicine; Psychiatry","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":[0.000965335,0.0005915572,0.0005513037,0.0007296611,0.0002061857,0.00065023,0.000465724,0.0007684511,0.001194261],"category_scores_gemma":[0.003032378,0.0001635888,0.0004888724,0.0003428697,0.0001557048,0.000309312,0.0003471057,0.0006718299,0.0003158694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005809687,"about_ca_system_score_gemma":0.0006819087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005019866,"about_ca_topic_score_gemma":0.003651529,"domain_scores_codex":[0.9996573,0.0001235005,0.00003114249,0.0000781533,0.00006138877,0.0000485526],"domain_scores_gemma":[0.9985359,0.001033278,0.0001214195,0.00003168596,0.0002240037,0.00005373212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004462019,0.0007700328,0.04851893,0.0001125095,0.0001931119,0.0003577609,0.00007817838,0.7501463,0.002763654,0.0006807476,0.002763458,0.1931692],"study_design_scores_gemma":[0.000006830846,0.00008170467,0.002354626,0.000009709403,0.00001161709,0.00002722021,0.000008705429,0.9968027,0.0002735067,0.0002849136,0.0001344191,0.000004019972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6073584,0.001281712,0.3832992,0.002245774,0.0002189723,0.0002949528,0.001021476,0.00154022,0.002739292],"genre_scores_gemma":[0.9712643,0.0001330338,0.02720112,0.0001305824,0.00005131173,0.0000994204,0.0003943739,0.000009491878,0.0007163101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005019866,"threshold_uncertainty_score":0.009981334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1158566415492074,"score_gpt":0.3037230320524615,"score_spread":0.1878663905032541,"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."}}