{"id":"W2299215064","doi":"10.2196/mhealth.5027","title":"Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion","year":2016,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Louisiana Clinical and Translational Science Center; University of California, Los Angeles; National Institutes of Health; Louisiana State University; U.S. Department of Agriculture","keywords":"mHealth; Weight management; Dashboard; Mobile phone; Computer science; Behavior change; Weight loss; Bluetooth; Multimedia; Medicine; Psychological intervention; Data science; Nursing; Wireless; Obesity; Telecommunications","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":[0.0005675228,0.0006885809,0.000424214,0.0006706623,0.0003263997,0.0004173313,0.0009694471,0.0006580938,0.019459],"category_scores_gemma":[0.001314211,0.0002215722,0.0007051246,0.0002211299,0.0002317536,0.0007651402,0.001590949,0.0006298297,0.002850144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002237671,"about_ca_system_score_gemma":0.0006426509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009298003,"about_ca_topic_score_gemma":0.001641491,"domain_scores_codex":[0.9996287,0.0001062533,0.00002281247,0.00007380421,0.0001211171,0.00004743629],"domain_scores_gemma":[0.9997419,0.0001023448,0.00002939728,0.00002159935,0.00003175959,0.00007307852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.003067253,0.006621429,0.004459548,0.0014672,0.0001714517,0.0002701866,0.0005725952,0.000954353,0.01851793,0.001137121,0.04446881,0.918292],"study_design_scores_gemma":[0.02525003,0.06766628,0.2003402,0.003115622,0.00274237,0.003827341,0.001717659,0.0764075,0.04920371,0.01314835,0.555769,0.0008118732],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6654207,0.004276342,0.2123104,0.007781725,0.001602329,0.01110469,0.007485364,0.03932696,0.05069152],"genre_scores_gemma":[0.6243123,0.003559283,0.287476,0.005415259,0.0006448503,0.01390601,0.004977289,0.0008018212,0.05890717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.019459,"threshold_uncertainty_score":0.06509686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09655992409835487,"score_gpt":0.4787303019647725,"score_spread":0.3821703778664176,"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."}}