{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007784947,0.0008432769,0.0007187134,0.001408631,0.003099787,0.001692369,0.003230664,0.0008597084,0.001486148],"category_scores_gemma":[0.01384036,0.0005264264,0.0008525057,0.004078955,0.00138452,0.0006198221,0.001067823,0.001268968,0.0004211814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04798399,"about_ca_system_score_gemma":0.04517064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934596,"about_ca_topic_score_gemma":0.994154,"domain_scores_codex":[0.994562,0.001165839,0.0003390459,0.0009308851,0.0020606,0.0009416906],"domain_scores_gemma":[0.9760914,0.002866708,0.003131899,0.001461559,0.01461995,0.001828457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001347108,0.0001295882,0.9922389,0.00004982034,0.000092002,0.00009328876,0.0004654511,0.0003601897,0.000256317,0.00009667646,0.002296249,0.00378671],"study_design_scores_gemma":[0.00004615694,0.00006089476,0.996265,0.00004511189,0.00003567035,0.00005303768,0.000507013,0.001791589,0.0001360719,0.00001350779,0.001031539,0.00001436699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794561,0.0004965897,0.001995922,0.000500871,0.00002842572,0.0008299584,0.01435138,0.00007096742,0.002269794],"genre_scores_gemma":[0.9824836,0.000309671,0.003634236,0.0005296634,0.00001398469,0.0004651056,0.01168351,0.00003356755,0.0008467703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04798399,"threshold_uncertainty_score":0.3481498,"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."}}