{"id":"W4295047764","doi":"10.21203/rs.3.rs-1726114/v1","title":"Predicting Hospital Admission among High Acuity Triaged Patients Transported to the Emergency Department in Ontario, Canada: A Population-Based Cohort Study using Machine Learning","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"McMaster University","keywords":"Emergency department; Triage; Medicine; Cohort; Emergency medicine; Medical emergency; Hospital admission; Population; Nursing; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0008238833,0.0004800114,0.0004505198,0.0009045145,0.001708671,0.00119247,0.001051264,0.0005789933,0.00120136],"category_scores_gemma":[0.00315035,0.0004569599,0.0006914361,0.002107235,0.0007800871,0.0005025422,0.0006729317,0.0008165825,0.0002015515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01066798,"about_ca_system_score_gemma":0.01319102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9284363,"about_ca_topic_score_gemma":0.9474726,"domain_scores_codex":[0.9989719,0.00007691619,0.00008123132,0.0002677459,0.0003417935,0.0002604315],"domain_scores_gemma":[0.9976727,0.0002082309,0.0005913456,0.000173991,0.0008928009,0.0004609185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004236197,0.00002673773,0.9987966,0.000009211647,0.00003314215,0.00003921457,0.0001261769,0.00007043164,0.00008027682,0.00001551742,0.0002030584,0.0005573738],"study_design_scores_gemma":[0.00001012476,0.00005492419,0.998209,0.00001513022,0.00003381536,0.00005371054,0.0003719378,0.0009110156,0.00003984776,0.00001846497,0.0002731832,0.00000875871],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978936,0.0001063634,0.0001331325,0.0000908186,0.000006900966,0.00004169188,0.001373206,0.000005429901,0.000348781],"genre_scores_gemma":[0.9984302,0.0001108189,0.0001680538,0.00004666716,0.000007324191,0.00002390056,0.0009538759,0.00000299247,0.0002560838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07156366,"threshold_uncertainty_score":0.1439702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0385265418702186,"score_gpt":0.3500902791211914,"score_spread":0.3115637372509728,"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."}}