{"id":"W4408519213","doi":"10.2337/dc25-0058","title":"Use of Medical Identification for People Living With Type 1 Diabetes: Results From the BETTER Registry","year":2025,"lang":"en","type":"letter","venue":"Diabetes Care","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; McGill University; Université de Montréal; University of Alberta; Montreal Clinical Research Institute","funders":"Novo Nordisk Canada; Breakthrough T1D Canada; Canadian Institutes of Health Research; Eli Lilly Canada; Diabète Québec","keywords":"Medicine; Type 2 diabetes; Diabetes mellitus; Identification (biology); MEDLINE; Gerontology; Family medicine; Internal medicine; Intensive care medicine; Endocrinology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002578886,0.0002223788,0.000628947,0.001107131,0.001037583,0.001256684,0.0006469002,0.003807859,0.003968185],"category_scores_gemma":[0.01340894,0.0003526196,0.0006629131,0.002387231,0.0003253347,0.001075443,0.000838001,0.001683833,0.001338376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00129653,"about_ca_system_score_gemma":0.002806485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04745005,"about_ca_topic_score_gemma":0.0856564,"domain_scores_codex":[0.9969636,0.001242233,0.0004691047,0.0002808024,0.0006739683,0.0003703359],"domain_scores_gemma":[0.9835012,0.006420175,0.004803161,0.001064463,0.002427879,0.001783099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003057312,0.0002162992,0.7672025,0.00009048115,0.00008234711,0.0005588214,0.0003196134,0.0001148732,0.0001375701,0.0003222214,0.2151604,0.01548917],"study_design_scores_gemma":[0.0002170978,0.0001414167,0.9710956,0.0002600814,0.0001230375,0.0006634033,0.00159537,0.0006981609,0.0001768814,0.0003904549,0.02458777,0.00005087053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5218986,0.004508096,0.0005465826,0.3410606,0.004239854,0.0002732067,0.08000132,0.000155706,0.04731594],"genre_scores_gemma":[0.7046899,0.004368989,0.001717311,0.2329952,0.006507006,0.00068717,0.02485235,0.00009048491,0.02409154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04745005,"threshold_uncertainty_score":0.09434772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02861308849402215,"score_gpt":0.2843302713259883,"score_spread":0.2557171828319661,"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."}}