{"id":"W2783252359","doi":"10.2196/mhealth.9236","title":"Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Russian Science Foundation","keywords":"Gestational diabetes; mHealth; Computer science; Recommender system; Software; Diabetes mellitus; Medicine; Pregnancy; Machine learning; Psychological intervention; Gestation","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":[],"consensus_categories":[],"category_scores_codex":[0.0008936499,0.0001028607,0.0002077741,0.0001397854,0.000180778,0.00001131587,0.00002305387,0.00003851318,0.00001213893],"category_scores_gemma":[0.00004930294,0.00008039553,0.00001468773,0.0001129479,0.0001035611,0.00006990585,0.00001448965,0.00005171395,0.00000123988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001338883,"about_ca_system_score_gemma":0.0006250636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001003602,"about_ca_topic_score_gemma":0.000009653732,"domain_scores_codex":[0.9983978,0.00006908247,0.0003072481,0.0002425651,0.0006940555,0.0002892511],"domain_scores_gemma":[0.9985076,0.00008330352,0.0001497283,0.00008485456,0.0008857075,0.0002888461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004450579,0.002846559,0.4887786,0.04788385,0.0006190557,0.00000115298,0.00970308,0.00001658903,0.0003798031,0.005925079,0.0009555478,0.4384401],"study_design_scores_gemma":[0.01032148,0.004168468,0.9768801,0.0003745094,0.000320706,0.000001311503,0.000728528,0.00388628,0.0003643224,0.00006278242,0.002802481,0.00008907769],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955606,0.001019625,0.0001001843,0.0001276986,0.00004068492,0.002936677,0.00009645029,0.00002193798,0.00009615967],"genre_scores_gemma":[0.9917279,0.0001278308,0.006388907,0.00009935236,0.0000645044,0.001088219,0.0004596622,0.00001210187,0.00003155949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4881015,"threshold_uncertainty_score":0.3278434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03898967738404178,"score_gpt":0.3545549508173871,"score_spread":0.3155652734333453,"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."}}