{"id":"W3042407815","doi":"10.2196/19892","title":"Decompensation in Critical Care: Early Prediction of Acute Heart Failure Onset","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; National Science Foundation","keywords":"Decompensation; Heart failure; Medicine; Intensive care unit; Myocardial infarction; Intensive care medicine; Risk factor; Logistic regression; Emergency medicine; Cardiology; Heart disease; Internal medicine; Vital signs; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001023366,0.0001089819,0.0003204899,0.00007720494,0.0000217955,0.00001165902,0.00006287674,0.0001774565,0.0002599284],"category_scores_gemma":[0.0003370144,0.00008672161,0.00008432895,0.0002219206,0.00009214337,0.0001495132,0.0000369649,0.0002613855,0.00006978585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006711185,"about_ca_system_score_gemma":0.0001527471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001527549,"about_ca_topic_score_gemma":0.000004253341,"domain_scores_codex":[0.9984344,0.00002612241,0.0006149645,0.00008367583,0.0006674958,0.0001733859],"domain_scores_gemma":[0.9991589,0.000174632,0.00006106417,0.0001419424,0.0001012482,0.0003621662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005875443,0.001469051,0.8675085,0.00244536,0.0003601952,0.0001557285,0.06235564,0.000006890395,0.0003184803,0.001111735,0.05255364,0.01112724],"study_design_scores_gemma":[0.009708866,0.00394311,0.9327238,0.001083553,0.0005166777,0.0001991939,0.01064911,0.01820282,0.00757924,0.00007969977,0.01500973,0.0003042592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839365,0.00004839418,0.0001972754,0.0148377,0.0000926862,0.0004047784,0.00006140424,0.00005066532,0.000370624],"genre_scores_gemma":[0.9924695,0.00002281628,0.003999868,0.00319598,0.00007845926,0.00006056733,0.0001628234,0.000008412636,0.000001538381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06521524,"threshold_uncertainty_score":0.3536405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05887880791557606,"score_gpt":0.3727713185122544,"score_spread":0.3138925105966783,"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."}}