{"id":"W2274212597","doi":"10.1177/1932296815599551","title":"Economic Value of Improved Accuracy for Self-Monitoring of Blood Glucose Devices for Type 1 Diabetes in Canada","year":2015,"lang":"en","type":"article","venue":"Journal of Diabetes Science and Technology","topic":"Diabetes Management and Research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bayer (Canada)","funders":"Bayer HealthCare; Public Health Agency of Canada","keywords":"Blood Glucose Self-Monitoring; Type 1 diabetes; Continuous glucose monitoring; Medicine; Diabetes mellitus; Type 2 diabetes; Blood glucose monitoring; Value (mathematics); Intensive care medicine; Emergency medicine; Endocrinology; Mathematics; Statistics","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":[0.004984968,0.0008682134,0.0008440917,0.000932876,0.0009999983,0.002320775,0.002058017,0.001061119,0.002935783],"category_scores_gemma":[0.02262027,0.0004985332,0.00144438,0.001168598,0.000986362,0.0007850432,0.001110131,0.001389324,0.0001367444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07772971,"about_ca_system_score_gemma":0.0609454,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.955541,"about_ca_topic_score_gemma":0.9213898,"domain_scores_codex":[0.9973841,0.001050006,0.00009191626,0.0002948803,0.0006647406,0.0005143328],"domain_scores_gemma":[0.9911573,0.004753789,0.0006959155,0.0003385291,0.00251155,0.0005429971],"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":[0.002069947,0.0002811099,0.0596453,0.0002896872,0.0004503971,0.0001458297,0.00008284405,0.9087507,0.0003268839,0.004727996,0.00364455,0.01958468],"study_design_scores_gemma":[0.001317884,0.0008951725,0.05350264,0.00021866,0.0007386191,0.0000978175,0.0001986064,0.9345267,0.0009572959,0.003415674,0.004012187,0.0001186965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9559001,0.002711153,0.008706464,0.004379126,0.0001389302,0.0008359848,0.008894257,0.0002207285,0.01821333],"genre_scores_gemma":[0.9944231,0.0004150239,0.002740871,0.0002267914,0.000007329341,0.00006229186,0.001140869,0.00001086203,0.0009728511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07772971,"threshold_uncertainty_score":0.5639712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308698983043917,"score_gpt":0.3042659434310598,"score_spread":0.2811789536006206,"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."}}