{"id":"W2948260946","doi":"10.2337/db19-213-lb","title":"213-LB: Developing a Prognostic Model to Assess Dysglycemia Risk in Canadians Aged 18-39","year":2019,"lang":"en","type":"article","venue":"Diabetes","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Diabetes mellitus; Young adult; Demography; Logistic regression; Odds ratio; Internal medicine; Area under the curve; Gerontology; Endocrinology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002507983,0.001268242,0.0006705894,0.002087604,0.00136872,0.001271699,0.001510879,0.0005606213,0.00314743],"category_scores_gemma":[0.004979625,0.0003333331,0.001354774,0.001214541,0.0003094282,0.0003774824,0.0009585958,0.0009086888,0.0005546805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006815384,"about_ca_system_score_gemma":0.01333373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8380249,"about_ca_topic_score_gemma":0.7317963,"domain_scores_codex":[0.9994747,0.0001339435,0.0000364678,0.0001029323,0.0001306905,0.0001212291],"domain_scores_gemma":[0.998692,0.0003236542,0.0001101362,0.00003300977,0.0006641397,0.000177082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000740954,0.000316759,0.8824086,0.0001253036,0.0005365163,0.0002159017,0.0002968384,0.03515226,0.0003490106,0.001006739,0.009636455,0.06921476],"study_design_scores_gemma":[0.0001703588,0.0003364548,0.2097433,0.0001614183,0.000499649,0.0001922987,0.0006847708,0.7812428,0.0003283625,0.00131371,0.005253102,0.00007379887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9218178,0.0009350265,0.05254611,0.003012192,0.0002047613,0.001047136,0.01180483,0.001198735,0.00743333],"genre_scores_gemma":[0.9536935,0.0003787112,0.03674401,0.0001714696,0.0000464989,0.0003945996,0.006107497,0.00004033657,0.002423382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1619751,"threshold_uncertainty_score":0.3258581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02654557477624813,"score_gpt":0.2586971852269199,"score_spread":0.2321516104506718,"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."}}