{"id":"W2342818888","doi":"10.1136/bmjdrc-2015-000134","title":"Blood glucose self-monitoring and internet diabetes management on A1C outcomes in patients with type 2 diabetes","year":2016,"lang":"en","type":"article","venue":"BMJ Open Diabetes Research & Care","topic":"Diabetes Management and Education","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"Diabetes mellitus; Type 2 diabetes; Medicine; Diabetes management; Blood Glucose Self-Monitoring; Type 1 diabetes; Internal medicine; Self-management; Intensive care medicine; Continuous glucose monitoring; Endocrinology; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001123943,0.0003505966,0.0005843475,0.0006112983,0.0001301437,0.0003517796,0.0006128942,0.0001015293,0.0001201673],"category_scores_gemma":[0.0003618438,0.000227744,0.00005556783,0.0006868826,0.0001445665,0.000525962,0.001040913,0.000304647,0.0001527048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003171469,"about_ca_system_score_gemma":0.00007576211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001606959,"about_ca_topic_score_gemma":0.00001051016,"domain_scores_codex":[0.9963064,0.0002376905,0.0003962629,0.0007852,0.001090874,0.001183586],"domain_scores_gemma":[0.9978659,0.0004044675,0.000106503,0.0008189874,0.0004951947,0.0003089998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001205349,0.0007435733,0.9565838,0.0006874657,0.0005025438,0.000009385954,0.0003899744,4.056899e-7,0.0001599724,0.00007845804,0.001160151,0.03956372],"study_design_scores_gemma":[0.004672974,0.002431566,0.9791605,0.002500936,0.0001410798,2.663581e-8,0.0006323499,0.000007064044,0.008149131,0.00007086898,0.001887592,0.0003458739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874304,0.0003552134,5.762705e-8,0.0007911391,0.0002722286,0.004588554,0.0000142602,0.00007208028,0.006476095],"genre_scores_gemma":[0.9954873,0.000112884,0.0004011962,0.0001473891,0.0001208219,0.001030804,0.00007786006,0.0000760648,0.002545635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03921785,"threshold_uncertainty_score":0.9287131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03710208823516729,"score_gpt":0.3719447156616388,"score_spread":0.3348426274264715,"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."}}