{"id":"W3034903360","doi":"10.2337/db20-393-p","title":"393-P: Technology Use and Hypoglycemia in Type 1 Diabetes: Insights from the BETTER Registry","year":2020,"lang":"en","type":"article","venue":"Diabetes","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hypoglycemia; Medicine; Pediatrics; Continuous glucose monitoring; Type 2 Diabetes Mellitus; Type 1 diabetes; Diabetes mellitus; 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":[0.003828933,0.0002121471,0.0004979432,0.003051403,0.001161977,0.002129298,0.0007540693,0.0005672697,0.007128924],"category_scores_gemma":[0.0202214,0.0002414594,0.0008205073,0.01174807,0.0002654853,0.001596115,0.001827377,0.0009443046,0.001237825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00263416,"about_ca_system_score_gemma":0.004782779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2075977,"about_ca_topic_score_gemma":0.230632,"domain_scores_codex":[0.9970432,0.0009299673,0.0004328034,0.0002978708,0.0007921279,0.0005039688],"domain_scores_gemma":[0.9751307,0.006336313,0.008805375,0.00180754,0.005321575,0.002598374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001850741,0.000133831,0.9567217,0.0001425111,0.00006786857,0.00004580503,0.0004797757,0.00009494735,0.00002370293,0.0002390571,0.02062067,0.02124499],"study_design_scores_gemma":[0.00002472151,0.00006410016,0.9883592,0.0001753104,0.0000548522,0.00007904587,0.0008489217,0.0001907959,0.00003180211,0.00008062928,0.01007194,0.00001864215],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7532768,0.003615744,0.0008337961,0.006671801,0.0001356128,0.0005452505,0.2054271,0.0001348676,0.02935906],"genre_scores_gemma":[0.893093,0.003828553,0.002727952,0.002003904,0.000267595,0.0008091732,0.09275523,0.0001046938,0.004409879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2075977,"threshold_uncertainty_score":0.4127786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02725014449163662,"score_gpt":0.2498026330031577,"score_spread":0.2225524885115211,"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."}}