{"id":"W4285388925","doi":"10.2337/dc21-2341","title":"Population-Level Impact and Cost-effectiveness of Continuous Glucose Monitoring and Intermittently Scanned Continuous Glucose Monitoring Technologies for Adults With Type 1 Diabetes in Canada: A Modeling Study","year":2022,"lang":"en","type":"article","venue":"Diabetes Care","topic":"Diabetes Management and Research","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; York University","funders":"","keywords":"Medicine; Continuous glucose monitoring; Type 1 diabetes; Blood Glucose Self-Monitoring; Population; Quality-adjusted life year; Cohort; Cost effectiveness; Diabetes mellitus; Emergency medicine; Pediatrics; Internal medicine; Environmental health; Endocrinology; Risk analysis (engineering)","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":[0.002697256,0.001284109,0.001531947,0.001524667,0.001359552,0.002060603,0.002745812,0.001761665,0.004156256],"category_scores_gemma":[0.008136499,0.0007774838,0.002988131,0.002530342,0.001003585,0.0007607355,0.0008839171,0.001604346,0.0002263657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05299515,"about_ca_system_score_gemma":0.03901828,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.967164,"about_ca_topic_score_gemma":0.9379703,"domain_scores_codex":[0.9986982,0.000402708,0.00005026512,0.0001658424,0.0001618852,0.0005210594],"domain_scores_gemma":[0.9947399,0.002869017,0.0005783504,0.0001361268,0.001109671,0.0005668988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001482793,0.000617102,0.08518786,0.0003275197,0.001087157,0.0003645793,0.0001617835,0.8898126,0.0002578318,0.006962804,0.004606477,0.009131444],"study_design_scores_gemma":[0.001048781,0.0004170057,0.03601434,0.0001753672,0.001196886,0.0001319007,0.0003860247,0.9565337,0.0001607846,0.00177638,0.002075244,0.00008372221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9722507,0.002198777,0.003120096,0.002383548,0.00004884011,0.0004877873,0.01023128,0.0000730214,0.009206058],"genre_scores_gemma":[0.9917116,0.001042946,0.00226425,0.000239149,0.00001553967,0.0001660934,0.002320164,0.00001282438,0.002227548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05299515,"threshold_uncertainty_score":0.3845085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.024024545800914,"score_gpt":0.2916862396914379,"score_spread":0.2676616938905239,"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."}}