{"id":"W2416589431","doi":"10.1097/qmh.0000000000000067","title":"Causal Analysis of Emergency Department Delays","year":2015,"lang":"en","type":"article","venue":"Quality Management in Health Care","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Smiths Detection (Canada)","funders":"","keywords":"Emergency department; Root cause analysis; Root cause; Psychological intervention; Causal inference; Bayesian network; Causal analysis; Bayesian probability; Medicine; Computer science; Medical emergency; Operations management; Risk analysis (engineering); Nursing; Artificial intelligence; Engineering","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":[0.06577066,0.0008607846,0.0009422307,0.004887066,0.001252879,0.001808483,0.001715808,0.001381566,0.00593418],"category_scores_gemma":[0.2473695,0.0005376834,0.002964245,0.004488715,0.002053838,0.003759894,0.002312116,0.002553069,0.0001311704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003911411,"about_ca_system_score_gemma":0.005129101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01189314,"about_ca_topic_score_gemma":0.005606358,"domain_scores_codex":[0.9302511,0.05956545,0.002091378,0.003690241,0.003510662,0.0008911449],"domain_scores_gemma":[0.4814217,0.4784226,0.02184583,0.01016242,0.007241359,0.0009060676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001490993,0.0007371962,0.3781886,0.004193775,0.007164551,0.0008463886,0.003955041,0.1163147,0.000387118,0.3384817,0.007122603,0.1411175],"study_design_scores_gemma":[0.0005853787,0.0005639672,0.07059327,0.00149069,0.003244924,0.0004439235,0.002091576,0.2206336,0.001043459,0.6887999,0.01035903,0.0001504001],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3461537,0.007622971,0.6081999,0.01586687,0.0006921806,0.00168528,0.005047785,0.0004476343,0.01428367],"genre_scores_gemma":[0.9477389,0.001289337,0.04843728,0.0004730503,0.0001884347,0.0008006974,0.0005770382,0.00002433797,0.0004707365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06577066,"threshold_uncertainty_score":0.3478326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1053277428826816,"score_gpt":0.4443217055782884,"score_spread":0.3389939626956068,"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."}}