{"id":"W2748770582","doi":"10.2196/diabetes.8039","title":"One Drop | Mobile: An Evaluation of Hemoglobin A1c Improvement Linked to App Engagement","year":2017,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Type 2 diabetes; Diabetes mellitus; Mobile apps; Medicine; Data collection; Computer science; Statistics; World Wide Web; Mathematics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.004759918,0.0001975044,0.000416936,0.0001444829,0.001909146,0.0000243417,0.0005624747,0.0001744971,0.0007900887],"category_scores_gemma":[0.0004258076,0.0002004007,0.00005994007,0.0001376732,0.0000685234,0.0001947384,0.0002619083,0.0004597115,0.0004142479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003830122,"about_ca_system_score_gemma":0.0008592629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002831951,"about_ca_topic_score_gemma":0.0002318988,"domain_scores_codex":[0.9963356,0.0005688412,0.0009801157,0.0005167032,0.0007422635,0.0008564488],"domain_scores_gemma":[0.9957649,0.0002192681,0.0008087608,0.001777656,0.0007808918,0.0006485076],"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":[0.00005904613,0.00104443,0.06566148,0.001666574,0.00004706098,1.215481e-7,0.002253497,0.00005151055,0.03730636,0.002294535,0.009447941,0.8801674],"study_design_scores_gemma":[0.004338177,0.001434194,0.8176196,0.0006015821,0.0001552728,3.535873e-8,0.001368754,0.00417524,0.003402053,0.00277082,0.1636667,0.0004675385],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973803,0.0001524902,0.00007049736,0.001883636,0.0005363066,0.01883273,0.00008986922,0.0001174098,0.004514055],"genre_scores_gemma":[0.9061539,0.00005561462,0.001011125,0.001997449,0.0004393047,0.08974579,0.0001026816,0.00003567486,0.000458513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8796999,"threshold_uncertainty_score":0.9993902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1171739337803863,"score_gpt":0.4828674721002609,"score_spread":0.3656935383198747,"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."}}