{"id":"W2970155444","doi":"","title":"UTILIZING TECHNOLOGICAL DEVICES TO ENHANCE PREVENTION OF TYPE II DIABETES MELLITUS","year":2019,"lang":"en","type":"article","venue":"TopSCHOLAR (Western Kentucky University)","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Type 1 diabetes; Medicine; Type 2 Diabetes Mellitus; Diabetes mellitus; Computer science; 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":[0.0006296425,0.0003490567,0.0002655461,0.0005215617,0.000313962,0.0007251557,0.0002823222,0.0004414429,0.00601394],"category_scores_gemma":[0.001313868,0.0001358091,0.0003851345,0.0002659451,0.0001034498,0.0002765246,0.0004401346,0.0005410144,0.0008997018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000180878,"about_ca_system_score_gemma":0.0004495196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174205,"about_ca_topic_score_gemma":0.002935926,"domain_scores_codex":[0.9996792,0.000123336,0.00002152997,0.00004079919,0.00009385475,0.00004115999],"domain_scores_gemma":[0.9995953,0.00017898,0.00007320542,0.00001475433,0.0000709647,0.00006677225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001520236,0.009354479,0.05823327,0.001555161,0.0002487471,0.0001007715,0.000292725,0.0001622127,0.005263681,0.0002694915,0.009748334,0.9132509],"study_design_scores_gemma":[0.003399988,0.0538766,0.8125567,0.005310863,0.00176077,0.001231942,0.001523553,0.001851332,0.009443699,0.001087993,0.1078555,0.0001010739],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8838251,0.05515425,0.002705987,0.01018206,0.001177072,0.0009848555,0.0006902785,0.0002465583,0.0450338],"genre_scores_gemma":[0.8708102,0.08825471,0.01377466,0.003252884,0.000715771,0.001170905,0.0007712555,0.00003303098,0.02121674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00601394,"threshold_uncertainty_score":0.02011859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02229124911016051,"score_gpt":0.2900053707559824,"score_spread":0.2677141216458219,"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."}}