{"id":"W2948071322","doi":"10.1111/dme.14046","title":"Modelling potential cost savings from use of real‐time continuous glucose monitoring in pregnant women with Type 1 diabetes","year":2019,"lang":"en","type":"article","venue":"Diabetic Medicine","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Sunnybrook Hospital; University of Toronto; Mount Sinai Hospital","funders":"Breakthrough T1D Canada; Tommy's; Medtronic Europe; FedDev Ontario; Juvenile Diabetes Research Foundation Canada; National Institute for Health and Care Research; Sunnybrook Research Institute; Medtronic; Juvenile Diabetes Research Foundation International","keywords":"Medicine; Pregnancy; Type 1 diabetes; Continuous glucose monitoring; Cohort; Type 2 diabetes; Blood Glucose Self-Monitoring; Neonatal intensive care unit; Diabetes mellitus; Gestation; Emergency medicine; Obstetrics; Intensive care medicine; Pediatrics; Internal 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003616546,0.000207763,0.0006832679,0.0002870032,0.00002248718,0.00001587283,0.000128795,0.00006842074,0.0005204572],"category_scores_gemma":[0.0002086804,0.0001525208,0.0000289701,0.0003717716,0.0001363762,0.0001368076,0.00007146969,0.0002118439,0.00006631874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001485122,"about_ca_system_score_gemma":0.00008767924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005584651,"about_ca_topic_score_gemma":0.000001962712,"domain_scores_codex":[0.9977694,0.00006640593,0.0004306469,0.0003701636,0.0007596168,0.0006037679],"domain_scores_gemma":[0.9985746,0.0003348126,0.0001389021,0.0003935765,0.0002778644,0.0002802689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001407094,0.0006550856,0.6187909,0.001124798,0.0005780319,0.0001586552,0.002511416,0.01726321,0.3366711,0.00005879343,0.000450175,0.02033086],"study_design_scores_gemma":[0.0172025,0.008327486,0.7876535,0.01391227,0.0004229633,0.000002544318,0.001965691,0.141801,0.02574401,0.0005387564,0.001704945,0.0007243492],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997382,0.0005085653,0.0001057128,0.0002523246,0.0001484985,0.001112106,0.00001562525,0.00003454486,0.0004405807],"genre_scores_gemma":[0.9962156,0.0006811644,0.001420144,0.00008541421,0.0001171835,0.00007203497,0.0001322187,0.00003825235,0.001237919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.310927,"threshold_uncertainty_score":0.6219616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01939097858560849,"score_gpt":0.2527388840625318,"score_spread":0.2333479054769233,"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."}}