{"id":"W2565216079","doi":"10.2196/diabetes.6662","title":"DiaFit: The Development of a Smart App for Patients with Type 2 Diabetes and Obesity","year":2016,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences","keywords":"Type 2 diabetes; Mobile apps; Obesity; Diabetes mellitus; Self-management; Medicine; Diabetes management; Management of obesity; Internet privacy; Intensive care medicine; Computer science; Weight loss; World Wide Web; Internal medicine; Endocrinology","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":[0.001746789,0.001010108,0.0003185154,0.0008036087,0.0006297166,0.001035324,0.00126879,0.001048812,0.008852265],"category_scores_gemma":[0.007146753,0.0003527876,0.0008984366,0.0002764843,0.0003975055,0.001308674,0.002216785,0.001218346,0.002825259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002475879,"about_ca_system_score_gemma":0.001215368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007936009,"about_ca_topic_score_gemma":0.001320486,"domain_scores_codex":[0.9991859,0.0002913938,0.00009496382,0.0001392064,0.0001994165,0.00008917641],"domain_scores_gemma":[0.9974687,0.001604,0.0001316686,0.0001485181,0.0003105886,0.0003365296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001371114,0.001816921,0.02145876,0.002376687,0.0001227267,0.002299855,0.006971116,0.001400386,0.01619945,0.002445607,0.1516871,0.7918502],"study_design_scores_gemma":[0.001783464,0.006923175,0.06622829,0.003695328,0.0006719133,0.01615764,0.004801772,0.03215348,0.03898207,0.01096953,0.8167405,0.0008929676],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4042913,0.005151963,0.3909424,0.01415221,0.003562632,0.01532002,0.01210461,0.07023915,0.08423568],"genre_scores_gemma":[0.3254279,0.003127851,0.601614,0.006843472,0.0005539851,0.0104723,0.008408873,0.002987692,0.04056394],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008852265,"threshold_uncertainty_score":0.02961379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235093917382713,"score_gpt":0.3432879167124168,"score_spread":0.3209369775385897,"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."}}