{"id":"W4324355684","doi":"10.3390/pharmacy11020053","title":"Comparison of Fracture Identification Using Different Definitions in Healthcare Administrative (Claims) Data","year":2023,"lang":"en","type":"article","venue":"Pharmacy","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Women's College Hospital; Public Health Ontario; University of Toronto","funders":"Leslie Dan Faculty of Pharmacy, University of Toronto; Canadian Institutes of Health Research; University of Toronto","keywords":"Medicine; Hip fracture; Ulna; Emergency department; Incidence (geometry); Cohort; Emergency medicine; Surgery; Physical therapy; Internal medicine; Osteoporosis","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1975119,0.001298592,0.003060062,0.01590382,0.0006534813,0.005458472,0.003413236,0.001507705,0.0009104641],"category_scores_gemma":[0.4115165,0.00138842,0.006484665,0.0161924,0.00158567,0.002574397,0.002879623,0.001569004,0.0002301957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001974261,"about_ca_system_score_gemma":0.001851942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00449823,"about_ca_topic_score_gemma":0.006523374,"domain_scores_codex":[0.6389269,0.2369229,0.06716984,0.02090022,0.03423207,0.001848101],"domain_scores_gemma":[0.5237544,0.3564992,0.0704117,0.01613876,0.0326599,0.0005360718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001963192,0.0001352925,0.8684061,0.0185405,0.04639659,0.0001665568,0.00254625,0.001405972,0.0004717438,0.002087303,0.001730749,0.05614977],"study_design_scores_gemma":[0.000443663,0.001496546,0.9278378,0.01571732,0.02709433,0.001347176,0.004052914,0.004275349,0.002736047,0.003233005,0.01142455,0.0003412461],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7059664,0.2048348,0.06063599,0.002113555,0.001180689,0.002215696,0.01523711,0.0001656723,0.00765007],"genre_scores_gemma":[0.9423358,0.01930419,0.02526589,0.001372669,0.000485403,0.001639096,0.009219952,0.0001298926,0.0002471311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1975119,"threshold_uncertainty_score":0.9896107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6213421407944497,"score_gpt":0.5932046914910359,"score_spread":0.02813744930341378,"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."}}