{"id":"W4385449689","doi":"10.2196/45257","title":"Machine Learning Models Versus the National Early Warning Score System for Predicting Deterioration: Retrospective Cohort Study in the United Arab Emirates","year":2023,"lang":"en","type":"article","venue":"JMIR AI","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tamkeen; York University; New York University Abu Dhabi; Cleveland Clinic","keywords":"Early warning score; Medicine; Vital signs; Abu dhabi; Retrospective cohort study; Emergency medicine; Cohort; Emergency department; Warning system; Cohort study; Medical emergency; Internal medicine; Surgery","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.000948637,0.0001350269,0.0002111603,0.0001589279,0.0003582156,0.0000818688,0.00009650704,0.0000471147,0.000005639637],"category_scores_gemma":[0.0002340274,0.0000769741,0.00006760822,0.0007236222,0.00002314986,0.0001016973,0.00003140609,0.0002724439,0.00001077427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003239548,"about_ca_system_score_gemma":0.00005125639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002187458,"about_ca_topic_score_gemma":0.00007809896,"domain_scores_codex":[0.9986507,0.000152122,0.000246256,0.0002570022,0.0005045412,0.0001893778],"domain_scores_gemma":[0.9989294,0.0005626012,0.0001046689,0.0001447826,0.0002301332,0.00002842503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002122401,0.0001458888,0.9888719,0.00002171981,0.0001745474,0.00001697646,0.00572236,0.004243585,0.00001649605,0.0003241115,0.0001580773,0.00009211226],"study_design_scores_gemma":[0.002692317,0.0009361252,0.8620442,0.0001170052,0.0001038055,0.000005816696,0.004927134,0.1289709,0.00001768021,0.00005658119,0.00006352317,0.00006483565],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954844,0.00004852503,0.00003181956,0.000908414,0.0001291478,0.002814986,0.0000134495,0.0001385271,0.0004306941],"genre_scores_gemma":[0.9968893,0.000007225872,0.00001318854,0.0001270136,0.0001867285,0.00253266,0.0001476716,0.00002198275,0.00007422687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1268277,"threshold_uncertainty_score":0.3138913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.145280695388654,"score_gpt":0.3718261755518861,"score_spread":0.2265454801632321,"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."}}