{"id":"W2973224614","doi":"10.2147/clep.s217969","title":"<p>Identifying pediatric diabetes cases from health administrative data: a population-based validation study in Quebec, Canada</p>","year":2019,"lang":"en","type":"article","venue":"Clinical Epidemiology","topic":"Diabetes and associated disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Children's Hospital of Eastern Ontario; University of Ottawa; Centre hospitalier de l'Université Laval; Centre Hospitalier Universitaire Sainte-Justine; Montreal Children's Hospital; Institut National de Santé Publique du Québec; Centre Hospitalier Universitaire de Sherbrooke; McGill University Health Centre","funders":"Ministère de la Santé; Ministère de la Santé et des Services sociaux","keywords":"Medicine; Population; Incidence (geometry); Confidence interval; Disease; Type 2 diabetes; Diabetes mellitus; Pediatrics; Environmental health; Gerontology; Internal medicine","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003447328,0.0002689963,0.001011562,0.00006735326,0.00008836851,0.00002146749,0.0004779736,0.0003359201,0.00006266499],"category_scores_gemma":[0.01172354,0.0002606185,0.0001352616,0.0001946709,0.00005630646,0.00001716311,0.0002129452,0.0002729287,0.00001794829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001146637,"about_ca_system_score_gemma":0.001429164,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3002904,"about_ca_topic_score_gemma":0.9171463,"domain_scores_codex":[0.9937147,0.002636956,0.001760947,0.001119985,0.0001594508,0.0006079273],"domain_scores_gemma":[0.9936475,0.00427198,0.0009162528,0.0008767692,0.00007675257,0.0002107217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004676911,0.0003738634,0.9899439,0.00002076498,0.00008760741,0.00000452913,0.00001178142,0.0003740189,0.0001038389,0.0000203358,0.007865369,0.001147226],"study_design_scores_gemma":[0.001475097,0.0005895962,0.9933502,0.00002201941,0.00005169619,1.206453e-7,0.0001101387,0.0008540595,0.00002286121,0.0001313419,0.003109208,0.0002836456],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945837,0.001765652,0.00005418407,0.001762352,0.0007790265,0.0006324278,0.0003667318,0.00001696163,0.00003892568],"genre_scores_gemma":[0.9891171,0.0002067938,0.0002328869,0.002801035,0.0003720738,0.00003478432,0.007039447,0.0000269113,0.0001689348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6168559,"threshold_uncertainty_score":0.9999846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1170428795487252,"score_gpt":0.4149209764108332,"score_spread":0.297878096862108,"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."}}