{"id":"W2804856485","doi":"10.1093/pch/pxy054.027","title":"DEFINING PEDIATRIC DIABETES USING EMR RECORDS AND VALIDATION FROM LINKABLE MANITOBA COHORT DATA","year":2018,"lang":"en","type":"article","venue":"Paediatrics & Child Health","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Manitoba","funders":"","keywords":"Medicine; Diabetes mellitus; Medical record; Pediatrics; Cohort; Electronic medical record; Population; Primary care; Type 2 diabetes; Family medicine; Electronic health record; Health care; Internal medicine; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"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":[0.008874672,0.0006049486,0.0004277994,0.003461423,0.001355549,0.001571222,0.002082199,0.0004614176,0.001671014],"category_scores_gemma":[0.02086364,0.000666811,0.000722822,0.005306053,0.0006718129,0.0006339306,0.002156382,0.0009767667,0.0005711556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004977704,"about_ca_system_score_gemma":0.006469605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5697652,"about_ca_topic_score_gemma":0.6025515,"domain_scores_codex":[0.9939865,0.002476645,0.0006862798,0.0009400055,0.001254496,0.0006560188],"domain_scores_gemma":[0.9819428,0.002564738,0.005408573,0.003234301,0.006054185,0.0007953622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002885847,0.00003055996,0.997692,0.00002520797,0.00007120702,0.00004392199,0.0003098976,0.0001120001,0.00009261099,0.00004623073,0.0003451352,0.001202366],"study_design_scores_gemma":[0.00001806121,0.0000328807,0.9972556,0.00008428864,0.00005058589,0.00008071816,0.000594845,0.0004844409,0.0001567896,0.00003192655,0.001203708,0.000006160842],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845175,0.0003795119,0.00179736,0.0001865617,0.00002302553,0.0005975362,0.01064224,0.00003069905,0.001825631],"genre_scores_gemma":[0.978685,0.0004253005,0.004097471,0.0002297521,0.00002099671,0.0007389082,0.01517123,0.00001955209,0.0006117458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4302348,"threshold_uncertainty_score":0.865537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04697268112448003,"score_gpt":0.3297851274811351,"score_spread":0.2828124463566551,"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."}}