{"id":"W2947491138","doi":"10.1186/s12891-019-2568-2","title":"Identifying musculoskeletal conditions in electronic medical records: a prevalence and validation study using the Deliver Primary Healthcare Information (DELPHI) database","year":2019,"lang":"en","type":"article","venue":"BMC Musculoskeletal Disorders","topic":"Musculoskeletal Disorders and Rehabilitation","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Family Medicine; Western University","funders":"Lawson Health Research Institute","keywords":"Medicine; Medical diagnosis; Diagnosis code; Medical record; Epidemiology; Database; Family medicine; Health care; Pediatrics; Population; Internal medicine; Pathology; Environmental health","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00157042,0.0004127651,0.0004933953,0.0004958087,0.0002986178,0.00008352968,0.0002507774,0.0002251315,0.0004515013],"category_scores_gemma":[0.0005393285,0.0003242041,0.0003295026,0.0008584163,0.0002536506,0.001530999,0.000210112,0.0007714842,0.00006705668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003142464,"about_ca_system_score_gemma":0.000565781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001254676,"about_ca_topic_score_gemma":0.00227673,"domain_scores_codex":[0.9957823,0.0006507638,0.000959824,0.0006590451,0.001247048,0.000701037],"domain_scores_gemma":[0.9982404,0.0003443802,0.0002802551,0.0007087425,0.0001831508,0.0002430604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002787793,0.001101345,0.9696977,0.009559642,0.0001330788,0.000003635301,0.00332392,0.0001734262,0.0004416831,0.001290247,0.00008140808,0.01391519],"study_design_scores_gemma":[0.004374319,0.001104274,0.9757718,0.0006227102,0.0002228778,0.00002553728,0.01051917,0.006124007,0.000002568003,0.0006322456,0.0001446921,0.0004557846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909453,0.001048237,0.001659097,0.0008732264,0.0002963867,0.004692054,0.00002841256,0.00009418276,0.0003631332],"genre_scores_gemma":[0.9974188,0.0009704339,0.0003498499,0.0003041483,0.00006536766,0.0002575951,0.0005328148,0.00004424811,0.00005674986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01345941,"threshold_uncertainty_score":0.999921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704515640847684,"score_gpt":0.3232837733767223,"score_spread":0.3062386169682454,"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."}}