{"id":"W2114341353","doi":"10.1007/bf03405564","title":"Validity of Administrative Data Claim-based Methods for Identifying Individuals with Diabetes at a Population Level","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Public Health","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Calgary Laboratory Services; Alberta Health Services; University of Calgary","funders":"Fondation pour la Recherche Médicale; Calgary Laboratory Services; Alberta Health Services; Canadian Diabetes Association","keywords":"Medicine; Diabetes mellitus; Reference data; Population; Computer science; Data mining; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.01112063,0.0001613368,0.0007887669,0.0005244277,0.0002238482,0.00007570769,0.0003535433,0.0001266704,0.00008315851],"category_scores_gemma":[0.0032307,0.0001321648,0.0002009309,0.0003163924,0.0001486715,0.0003678337,0.0000210881,0.0004263408,7.288004e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003181915,"about_ca_system_score_gemma":0.01110231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02055995,"about_ca_topic_score_gemma":0.2154482,"domain_scores_codex":[0.997566,0.000491053,0.0007168978,0.0002439443,0.0003856887,0.0005963691],"domain_scores_gemma":[0.9957623,0.0003433581,0.0007907361,0.0006693606,0.000602213,0.001832049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003162942,0.0000998063,0.4791024,0.000774231,0.0007010785,0.00001530733,0.0008127877,0.000004449078,0.0001727321,0.0002824713,0.003022092,0.514981],"study_design_scores_gemma":[0.002802775,0.001319291,0.9114344,0.0003187502,0.0002684869,0.00007300716,0.0003538755,0.0002912643,0.001360723,0.0002535247,0.08132021,0.0002037524],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9461689,0.0005793293,0.04512327,0.005870113,0.0005067385,0.0008373811,0.0008431115,0.000009000309,0.00006218073],"genre_scores_gemma":[0.8563725,0.00000559442,0.1422704,0.000566566,0.0003195959,0.00001089659,0.0003908466,0.00002921012,0.00003444059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5147773,"threshold_uncertainty_score":0.9945038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3945264602987313,"score_gpt":0.4528601128556453,"score_spread":0.05833365255691403,"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."}}