{"id":"W2887581276","doi":"10.11159/icbes18.156","title":"Monitoring System for Glycemic Control in Patients with Type 2 Diabetes Mellitus, Based on Mobile Technology, Telemetry, and Health Education","year":2018,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Glycemic; Telemetry; Type 2 Diabetes Mellitus; Diabetes mellitus; Medicine; Computer science; Endocrinology; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000799541,0.000747349,0.0008176472,0.001927709,0.0005309524,0.001151803,0.0005104294,0.0006105911,0.004599335],"category_scores_gemma":[0.002343242,0.0001405822,0.0003709532,0.001100581,0.0000971543,0.0005310465,0.0005954891,0.0006186671,0.002091469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003949271,"about_ca_system_score_gemma":0.0006061303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003166977,"about_ca_topic_score_gemma":0.003282105,"domain_scores_codex":[0.9992576,0.0001424258,0.0001178714,0.000202504,0.0002291463,0.0000502787],"domain_scores_gemma":[0.9991517,0.0002138007,0.0001742938,0.00005787445,0.0003100803,0.00009228162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00372771,0.001678547,0.3552695,0.0009605986,0.000464224,0.001367721,0.001017783,0.001387925,0.01925055,0.0008663954,0.06756219,0.5464468],"study_design_scores_gemma":[0.001044755,0.003131769,0.7919248,0.0008462468,0.001388521,0.005153118,0.001072116,0.0756921,0.04259789,0.001883672,0.07490974,0.0003552116],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.767395,0.01728214,0.07883754,0.005455445,0.002193941,0.003518,0.03509336,0.03081207,0.05941258],"genre_scores_gemma":[0.9439,0.002843121,0.03406018,0.001732699,0.0006191005,0.001223426,0.00736083,0.000189205,0.00807146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004599335,"threshold_uncertainty_score":0.01538628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602835232407057,"score_gpt":0.3152939351988722,"score_spread":0.2992655828748016,"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."}}