{"id":"W4401414558","doi":"10.1371/journal.pone.0307845","title":"Surgeon- and hospital-level variation in wait times for scheduled non-urgent surgery in Ontario, Canada: A cross-sectional population-based study","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario; Women's College Hospital; Nova Scotia Health Authority; Learning Partnership; Public Health Ontario; University of British Columbia; Queen's University; University Health Network; Toronto General Hospital; Dalhousie University; University of Toronto; Sinai Health System","funders":"Canadian Institutes of Health Research; Ontario Ministry of Health and Long-Term Care","keywords":"Medicine; Cataract surgery; Arthroplasty; Population; Cross-sectional study; Surgery; General surgery","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001577767,0.0001473151,0.0003437616,0.0003385067,0.0003932861,0.00006036538,0.00004694128,0.0001687043,0.0004736966],"category_scores_gemma":[0.0008072311,0.0001515986,0.00003193654,0.0003601141,0.000007381721,0.0001914617,0.00002025498,0.0004273111,0.000005420577],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666716,"about_ca_system_score_gemma":0.007260218,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9333079,"about_ca_topic_score_gemma":0.9905579,"domain_scores_codex":[0.9978086,0.0002217575,0.0008709268,0.0004024442,0.0003460247,0.0003502757],"domain_scores_gemma":[0.9980811,0.001247527,0.0001006975,0.00015516,0.000291342,0.0001241626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004883484,0.0008820986,0.9948384,0.0002994035,0.0000412659,0.000005197451,0.001154744,0.002365356,0.00001480182,0.0002256988,0.00009342605,0.00003072812],"study_design_scores_gemma":[0.0005753292,0.00005769202,0.8933451,0.0003618419,0.00001506918,6.588964e-8,0.0001474168,0.105266,0.000003882574,0.00006169921,0.00002071305,0.000145156],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994963,0.00004527064,0.0005357802,0.001387462,0.0005255605,0.00239565,0.00008094473,0.00003842003,0.0000278775],"genre_scores_gemma":[0.9944814,0.000004795722,0.002902602,0.0001944381,0.0001049209,0.001092599,0.000460177,0.00002936252,0.0007297018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1029007,"threshold_uncertainty_score":0.9983677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1190275415906941,"score_gpt":0.354203796701704,"score_spread":0.2351762551110099,"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."}}