{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01106121,0.001352538,0.001556674,0.002150666,0.0007301456,0.002437284,0.001564283,0.001762104,0.006898727],"category_scores_gemma":[0.05997835,0.0004451571,0.004034731,0.001247289,0.0005604791,0.002235226,0.002237648,0.00169991,0.001058085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001126651,"about_ca_system_score_gemma":0.001943824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003099902,"about_ca_topic_score_gemma":0.005186423,"domain_scores_codex":[0.9872438,0.007007306,0.001483073,0.0009498114,0.002827605,0.0004883199],"domain_scores_gemma":[0.9592644,0.02877271,0.004643559,0.001388099,0.004150799,0.001780507],"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":[0.06866468,0.01980254,0.07162175,0.03704801,0.009862047,0.0003306796,0.002822132,0.0008107368,0.002162214,0.001037571,0.02824535,0.7575924],"study_design_scores_gemma":[0.07249473,0.1900609,0.5366297,0.03268996,0.04447525,0.00115756,0.003303635,0.009546035,0.006459518,0.003480504,0.09862833,0.001073905],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8858603,0.03593842,0.007017548,0.005770442,0.001440744,0.02297309,0.01625597,0.003019854,0.02172366],"genre_scores_gemma":[0.8804819,0.02048573,0.03917363,0.007009102,0.001216509,0.03540189,0.01011797,0.000470918,0.005642412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01106121,"threshold_uncertainty_score":0.05849797,"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."}}