{"id":"W2998307466","doi":"10.2196/16117","title":"Predicting Adverse Outcomes for Febrile Patients in the Emergency Department Using Sparse Laboratory Data: Development of a Time Adaptive Model","year":2019,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Emergency department; Receiver operating characteristic; Retrospective cohort study; Intensive care unit; Cohort; Emergency medicine; Adverse effect; 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":[0.0005423907,0.0001612701,0.0003768659,0.00008164608,0.00004847026,0.000004405183,0.0002328976,0.0001015001,0.0001098217],"category_scores_gemma":[0.0001695499,0.00009927316,0.00006359903,0.0001567767,0.000030791,0.0002202722,0.0001447396,0.0001289951,0.00003444767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001306907,"about_ca_system_score_gemma":0.0004574546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009232315,"about_ca_topic_score_gemma":0.00001498416,"domain_scores_codex":[0.9978446,0.00002359674,0.0009264589,0.0001231486,0.0008345089,0.0002477218],"domain_scores_gemma":[0.9988869,0.0001370608,0.0002792484,0.0004337906,0.0001355632,0.0001273684],"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":[0.0002165647,0.002738481,0.9694036,0.0005391404,0.0003901605,0.000004585758,0.01817742,0.0004485367,0.00001196015,0.00005416781,0.003772997,0.004242348],"study_design_scores_gemma":[0.006878965,0.0004008472,0.1504407,0.0005202872,0.0002003126,0.000002547604,0.004474618,0.834985,0.0002498818,0.00001861132,0.001594082,0.0002342175],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970245,0.0000250046,0.0003954917,0.00006484236,0.000110849,0.001890817,0.0001873511,0.00001540516,0.0002857212],"genre_scores_gemma":[0.9769883,0.00002636886,0.02142752,0.000654074,0.00002818619,0.0002307073,0.0006000224,0.00001647355,0.00002834694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8345364,"threshold_uncertainty_score":0.4048242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102089934099567,"score_gpt":0.3634012193315466,"score_spread":0.2613112852319796,"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."}}