{"id":"W3143650267","doi":"10.2196/25066","title":"Predicting Intensive Care Transfers and Other Unforeseen Events: Analytic Model Validation Study and Comparison to Existing Methods","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Michigan Institute for Data Science, University of Michigan; National Institutes of Health","keywords":"Intensive care unit; Medicine; Receiver operating characteristic; Intensive care; Emergency medicine; Health care; Coronavirus disease 2019 (COVID-19); Medical emergency; Test (biology); Intensive care medicine; Disease; Internal medicine","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":[0.0003624389,0.0001556723,0.0004373089,0.0001007852,0.00008660299,0.00003476828,0.00004844404,0.00009912425,0.00003134959],"category_scores_gemma":[0.0008303839,0.0001201185,0.00004709157,0.0001999433,0.00004155748,0.00009832015,0.00008026996,0.0002133811,0.000003256458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007789222,"about_ca_system_score_gemma":0.0001125749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003157119,"about_ca_topic_score_gemma":0.00002726751,"domain_scores_codex":[0.998467,0.00006869714,0.0005981123,0.0001462023,0.0005233488,0.0001966058],"domain_scores_gemma":[0.9987577,0.0002347889,0.00007876795,0.0001828565,0.0003571016,0.0003887798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001102154,0.0004668996,0.6351617,0.0006924206,0.0005415269,0.00003764413,0.227492,0.0003011244,0.00003005232,0.00007681944,0.0003319037,0.1347577],"study_design_scores_gemma":[0.005092577,0.001159797,0.03354278,0.0009478529,0.0007646756,0.00008773046,0.4308047,0.5249821,0.001898258,0.00005810963,0.0003957365,0.0002656725],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988403,0.0001668119,0.008988486,0.0006728755,0.00004414051,0.0007977848,0.0000130179,0.00004022243,0.0008736493],"genre_scores_gemma":[0.981348,0.00002093285,0.01590608,0.002516198,0.00003397824,0.00009406541,0.0000400022,0.00001450687,0.00002628649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6016189,"threshold_uncertainty_score":0.4898289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1876355175496016,"score_gpt":0.4846892294764886,"score_spread":0.297053711926887,"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."}}