{"id":"W3098764791","doi":"10.4258/hir.2020.26.4.284","title":"Mortality Prediction from Hospital-Acquired Infections in Trauma Patients Using an Unbalanced Dataset","year":2020,"lang":"en","type":"article","venue":"Healthcare Informatics Research","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"Shiraz University","keywords":"Medicine; Sampling (signal processing); Support vector machine; Random forest; Cluster analysis; Emergency medicine; Artificial intelligence; Computer science","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":[0.0004469448,0.0001524356,0.000330428,0.0002183066,0.0003056575,0.00003496253,0.0001344103,0.0001375757,0.00006710747],"category_scores_gemma":[0.0004259298,0.0001441058,0.00004608868,0.0008856563,0.0001182569,0.0005650052,0.0001181536,0.0005021339,0.00003711032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002969947,"about_ca_system_score_gemma":0.000261311,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008894717,"about_ca_topic_score_gemma":0.001685011,"domain_scores_codex":[0.9973848,0.0001640519,0.0007952107,0.0002151165,0.0009104296,0.0005303403],"domain_scores_gemma":[0.9984449,0.00006264896,0.00008804385,0.0004085196,0.0005501684,0.0004457278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001372966,0.0005094383,0.9607196,0.0007708682,0.0000644182,0.0000104761,0.02088201,0.0001059178,0.00004285496,0.00002885609,0.005151606,0.01157659],"study_design_scores_gemma":[0.00190309,0.001756496,0.9659708,0.0001830366,0.0000226074,0.000001633429,0.008648232,0.01647274,0.00009229797,0.00008117222,0.004702105,0.0001658361],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929585,0.00008628184,0.0001014557,0.001339351,0.0003242196,0.0009473776,0.003757007,0.00007682312,0.0004089848],"genre_scores_gemma":[0.9907256,0.0001958282,0.0004361923,0.000415456,0.0001901639,0.00005208691,0.007965511,0.00001748095,0.000001692745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01636682,"threshold_uncertainty_score":0.9977052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2985585221558938,"score_gpt":0.4746541934280464,"score_spread":0.1760956712721526,"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."}}