{"id":"W2762768154","doi":"10.1136/bmjopen-2017-017869","title":"Feasibility of using administrative data for identifying medical reasons to delay hip fracture surgery: a Canadian database study","year":2017,"lang":"en","type":"article","venue":"BMJ Open","topic":"Hip and Femur Fractures","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Coastal Health Research Institute; Vancouver Coastal Health; Dalhousie University; University of Toronto; McGill University; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Hip fracture; Health services research; Database; Public health; Medical emergency; Internal medicine; Nursing; Osteoporosis","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":[0.0383996,0.001026342,0.001062221,0.005011744,0.003447074,0.004074272,0.005105437,0.001565188,0.001444922],"category_scores_gemma":[0.1501417,0.001351378,0.002050197,0.01461273,0.001528889,0.001596281,0.00279097,0.001879461,0.0002314524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03414838,"about_ca_system_score_gemma":0.04695165,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9698999,"about_ca_topic_score_gemma":0.9609179,"domain_scores_codex":[0.9559729,0.01234462,0.004601709,0.003973258,0.01979029,0.003317285],"domain_scores_gemma":[0.8536696,0.03900262,0.04054974,0.01139234,0.05011767,0.005267932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002004627,0.00007444848,0.9937572,0.0001264061,0.0002536772,0.00004168629,0.0004654515,0.0001695591,0.00003613926,0.0001784035,0.001176147,0.003520367],"study_design_scores_gemma":[0.0001278757,0.00009309516,0.991984,0.0002489743,0.0003410811,0.0001120857,0.001071739,0.003732345,0.0001050118,0.00008418287,0.002035209,0.0000643269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705325,0.002388072,0.001382573,0.002541129,0.00008623659,0.0009676014,0.0168146,0.00003823982,0.005249131],"genre_scores_gemma":[0.9899575,0.0008438686,0.002470591,0.0005982444,0.00003592922,0.0002767875,0.005544582,0.00001710123,0.0002554998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9698999,"threshold_uncertainty_score":0.247765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5892308581823144,"score_gpt":0.57900160520631,"score_spread":0.0102292529760043,"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."}}