{"id":"W4391452253","doi":"10.2196/48675","title":"Weight Loss Using an mHealth App Among Individuals With Obesity in Different Economic Regions of China: Cohort Study","year":2024,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Shanghai","keywords":"mHealth; Obesity; Mobile apps; Cohort; China; Cohort study; Medicine; Demography; Environmental health; Gerontology; Psychology; Computer science; Psychological intervention; Geography; World Wide Web; Psychiatry; Sociology; 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":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007471884,0.0005532681,0.0004406094,0.0009133389,0.001764456,0.0007348638,0.000431925,0.000486991,0.001786404],"category_scores_gemma":[0.0009405791,0.0005696225,0.00103827,0.001322353,0.0003804095,0.0007752665,0.0008383935,0.0008858463,0.0003011706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008782027,"about_ca_system_score_gemma":0.001341152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05515855,"about_ca_topic_score_gemma":0.07573978,"domain_scores_codex":[0.9995351,0.00004761432,0.00005096758,0.0001291803,0.00009197983,0.0001451665],"domain_scores_gemma":[0.9995033,0.00002785889,0.0001219951,0.00007144775,0.0001070705,0.0001682559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001514941,0.000170347,0.9972364,0.00004162514,0.0001028126,0.000117129,0.0004079624,0.00001642184,0.0002007652,0.00002700238,0.0003047026,0.001223269],"study_design_scores_gemma":[0.00002831606,0.0001412671,0.9986247,0.00001558321,0.0000873094,0.00008233103,0.0005583537,0.0001259548,0.00003857523,0.00001703754,0.0002719528,0.00000882971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988349,0.000139859,0.00005605568,0.0000467419,0.000008459729,0.00008765561,0.0004957123,0.000002784226,0.0003278131],"genre_scores_gemma":[0.9986256,0.0001311019,0.0001100557,0.00009491709,0.00001033695,0.0001142793,0.0005541783,0.000002595937,0.0003569312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05515855,"threshold_uncertainty_score":0.109675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05803870011367542,"score_gpt":0.4300053985686623,"score_spread":0.3719666984549869,"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."}}