{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002882419,0.00008626285,0.0002737195,0.0002129217,0.00008400413,0.00001120104,0.0001446052,0.00003860635,0.00009659688],"category_scores_gemma":[0.00009843127,0.00007722598,0.00002819531,0.0005185413,0.00004753237,0.0001047465,0.00008544738,0.0003670714,0.0000397823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008142935,"about_ca_system_score_gemma":0.0003557118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007997615,"about_ca_topic_score_gemma":0.0002581268,"domain_scores_codex":[0.9985881,0.0001079452,0.0004620423,0.0002457,0.0003338277,0.0002623509],"domain_scores_gemma":[0.9990461,0.0001508013,0.0001172356,0.0003944907,0.0001058749,0.0001855033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004085749,0.0007542548,0.9567991,0.001304431,0.00002990419,0.00002770541,0.001276371,0.00003042501,0.02608246,0.0002385914,0.00632638,0.006721777],"study_design_scores_gemma":[0.002391669,0.0001275771,0.9050143,0.0002702521,0.00005561125,0.00001110097,0.001098117,0.06207932,0.02585487,0.0004074555,0.002561771,0.0001279402],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985121,0.0004911175,0.00007947215,0.01328653,0.00009501349,0.0005503061,0.0002453968,0.00004038157,0.00009078791],"genre_scores_gemma":[0.997431,0.000472201,0.0000930374,0.000355146,0.00005974988,0.00002379573,0.00152295,0.00001293375,0.00002921249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06204889,"threshold_uncertainty_score":0.3149184,"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."}}