{"id":"W4313545772","doi":"10.2196/43991","title":"Glycemic Outcomes and Feature Set Engagement Among Real-Time Continuous Glucose Monitoring Users With Type 1 or Non–Insulin-Treated Type 2 Diabetes: Retrospective Analysis of Real-World Data","year":2023,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Diabetes Management and Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dexcom","keywords":"Medicine; Type 1 diabetes; Hypoglycemia; Glycemic; Continuous glucose monitoring; Context (archaeology); Insulin; Cohort; Retrospective cohort study; Type 2 diabetes; Diabetes mellitus; Internal medicine; Endocrinology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007565753,0.000399947,0.001286975,0.001349755,0.000145426,0.000102668,0.000437294,0.000119247,0.0001179128],"category_scores_gemma":[0.0002988016,0.0002718124,0.0001119287,0.006235473,0.0003140645,0.0002582935,0.0005799459,0.000407518,0.00004298408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001295334,"about_ca_system_score_gemma":0.00006896233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001751276,"about_ca_topic_score_gemma":0.0002012908,"domain_scores_codex":[0.9971555,0.000126135,0.0003921113,0.0008156227,0.0007211348,0.0007894733],"domain_scores_gemma":[0.9973388,0.0004533386,0.000270297,0.001324414,0.0003692315,0.0002438656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005157146,0.0001339936,0.9743052,0.0002793073,0.005751375,0.00005014234,0.0001974652,0.00001981408,0.005796127,0.000002083171,0.01185953,0.001089211],"study_design_scores_gemma":[0.001800094,0.001225269,0.9876239,0.0003279474,0.002684837,4.527171e-8,0.0003244749,0.003289119,0.001924094,0.000004316978,0.0004864372,0.0003094084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967101,0.00007808645,1.076695e-7,0.0001818655,0.00009761821,0.001172301,0.000840324,0.0002508157,0.0006687917],"genre_scores_gemma":[0.9865733,0.0005667898,0.0002047709,0.00002961698,0.0000949859,0.00007216357,0.005614836,0.00007115698,0.006772387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01331872,"threshold_uncertainty_score":0.9999734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04161985683057156,"score_gpt":0.3437463162906803,"score_spread":0.3021264594601087,"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."}}