{"id":"W4205741871","doi":"10.1016/j.injury.2022.01.008","title":"Pediatric severe traumatic brain injury mortality prediction determined with machine learning-based modeling","year":2022,"lang":"en","type":"article","venue":"Injury","topic":"Traumatic Brain Injury and Neurovascular Disturbances","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; Vector Institute","funders":"","keywords":"Glasgow Coma Scale; Medicine; Machine learning; Intensive care unit; Feature selection; Artificial intelligence; Emergency medicine; Intensive care medicine; Computer science; Surgery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007152505,0.0006709062,0.0004657145,0.000822419,0.0002565824,0.0005839189,0.0004101829,0.0004040998,0.001032495],"category_scores_gemma":[0.002388727,0.0001856448,0.0007546236,0.0004794172,0.0001123272,0.000414385,0.0003109459,0.0005950151,0.0002540803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005178136,"about_ca_system_score_gemma":0.0009021728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01092059,"about_ca_topic_score_gemma":0.006052156,"domain_scores_codex":[0.9997868,0.00006667634,0.00002204751,0.00005804305,0.00003034348,0.00003608663],"domain_scores_gemma":[0.9991947,0.0004645323,0.0001041461,0.0000396006,0.0001452669,0.00005181163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007768882,0.0003406706,0.4444495,0.00007339127,0.0002671228,0.0004426352,0.00008057374,0.4741902,0.001786005,0.001084771,0.002447364,0.0740609],"study_design_scores_gemma":[0.000007302334,0.00005602214,0.02061524,0.000008071671,0.00004298444,0.0000770699,0.00002947208,0.9781176,0.0005255115,0.0003234121,0.0001913279,0.000005919637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9440464,0.0005456295,0.05227185,0.0003675522,0.00005632342,0.00004308594,0.001074851,0.0002881355,0.001306184],"genre_scores_gemma":[0.9924359,0.0001731682,0.006242861,0.00001686673,0.00001712728,0.00002155532,0.0008161612,0.000009999977,0.0002663142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01092059,"threshold_uncertainty_score":0.02171403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03071524596319139,"score_gpt":0.2760966405577593,"score_spread":0.2453813945945679,"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."}}