{"id":"W3091109908","doi":"10.2196/21788","title":"Predictive Models of Mortality for Hospitalized Patients With COVID-19: Retrospective Cohort Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research; National Institute of General Medical Sciences; Multidisciplinary University Research Initiative; Massachusetts General Hospital; National Science Foundation; National Institutes of Health; Tongji University","keywords":"Medicine; Triage; Retrospective cohort study; Logistic regression; Context (archaeology); Cohort; Cohort study; Emergency medicine; Coronavirus disease 2019 (COVID-19); Severity of illness; Disease; Internal medicine; Infectious disease (medical specialty)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001168815,0.000257646,0.001135219,0.00008252732,0.0001095062,0.00001418757,0.0003084309,0.0001784936,0.000143875],"category_scores_gemma":[0.04557909,0.0001720357,0.0001782484,0.0004699055,0.0006176252,0.0002634289,0.0003191353,0.0005472359,0.000005821742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003428831,"about_ca_system_score_gemma":0.001348824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005694374,"about_ca_topic_score_gemma":0.000006277804,"domain_scores_codex":[0.9946712,0.00007306244,0.001254559,0.0002899357,0.00330003,0.0004112069],"domain_scores_gemma":[0.9945489,0.00181226,0.0004308853,0.000463751,0.001069491,0.001674712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002075243,0.001503443,0.979127,0.001701517,0.001031331,0.0000103511,0.01163189,0.0001354115,1.656188e-7,0.0001345814,0.002447479,0.0002015636],"study_design_scores_gemma":[0.01447215,0.01106308,0.8903387,0.0001282652,0.0003948542,2.333755e-7,0.002061608,0.08029276,0.000004185325,0.0004954069,0.0005470571,0.0002017283],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9254006,0.000006758905,0.06093791,0.002694928,0.0000528456,0.009688698,0.0003233981,0.0001432147,0.0007517023],"genre_scores_gemma":[0.991598,0.00003300836,0.000796859,0.00645642,0.00008980685,0.0008771538,0.0001045917,0.00002306228,0.00002113164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08878836,"threshold_uncertainty_score":0.9624604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05415609627711594,"score_gpt":0.4258591230202496,"score_spread":0.3717030267431337,"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."}}