{"id":"W2972623710","doi":"10.1097/pcc.0000000000002121","title":"A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting*","year":2019,"lang":"en","type":"article","venue":"Pediatric Critical Care Medicine","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Wellcome Trust","keywords":"Medicine; Triage; Receiver operating characteristic; Psychological intervention; Referral; Emergency medicine; Mortality rate; Vital signs; Mechanical ventilation; Pediatrics; Acute care; Internal medicine; Surgery; Health care","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":[0.003125911,0.0005563906,0.0006648974,0.0006470624,0.0001810595,0.0004524899,0.0005453762,0.0004780381,0.001221497],"category_scores_gemma":[0.01004537,0.0002940009,0.000700818,0.000373082,0.0001905777,0.0006361736,0.0003328181,0.0007550155,0.0001759515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003882635,"about_ca_system_score_gemma":0.0009988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001447073,"about_ca_topic_score_gemma":0.002343521,"domain_scores_codex":[0.9987152,0.000899623,0.00009314438,0.0001057656,0.000122326,0.00006414308],"domain_scores_gemma":[0.9954669,0.002810619,0.001090912,0.000150551,0.0002038597,0.0002770436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02542117,0.005557124,0.6774869,0.001129852,0.000738355,0.0003302463,0.0003843854,0.02000794,0.002667117,0.0002999446,0.002957362,0.2630197],"study_design_scores_gemma":[0.015966,0.07044589,0.6303902,0.001025386,0.001544257,0.00115322,0.0007316981,0.2697479,0.004914235,0.0009402087,0.002958752,0.000182312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907679,0.0006010379,0.006340257,0.0005202388,0.00004709866,0.000657655,0.0004647223,0.0001315385,0.0004694335],"genre_scores_gemma":[0.9782376,0.0002717072,0.02013918,0.0001108008,0.00003794255,0.0006969448,0.0003850705,0.000007879056,0.0001130031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003125911,"threshold_uncertainty_score":0.01653159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01662776058028962,"score_gpt":0.32213720369861,"score_spread":0.3055094431183203,"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."}}