{"id":"W4384026751","doi":"10.2196/47473","title":"The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study","year":2023,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"EVERSANA (Canada)","funders":"","keywords":"Medicine; Overweight; Weight loss; Health care; Telehealth; Weight management; Retrospective cohort study; Obesity; Body mass index; Medical prescription; Gerontology; Demography; Emergency medicine; Telemedicine; Internal medicine; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001727476,0.0003278571,0.0005086014,0.001712877,0.000457902,0.001006836,0.0004945601,0.000420736,0.001170618],"category_scores_gemma":[0.006020607,0.0004025568,0.001859537,0.002290744,0.0003781131,0.0005696401,0.000791891,0.0005660802,0.0002088807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000822785,"about_ca_system_score_gemma":0.0006905806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008017278,"about_ca_topic_score_gemma":0.007318042,"domain_scores_codex":[0.9976598,0.0007739604,0.0004592851,0.0004083645,0.0004904456,0.0002080805],"domain_scores_gemma":[0.9930804,0.001303278,0.004048173,0.0004905892,0.0006408424,0.0004367903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002775895,0.00009675285,0.9979396,0.0000385843,0.0002575673,0.00002280946,0.00004245593,0.00003591113,0.0000292247,0.00001347185,0.00007495407,0.001171008],"study_design_scores_gemma":[0.00002773111,0.0004707449,0.9981522,0.00003048096,0.0002925747,0.0001855031,0.0002048426,0.0002670164,0.00007622519,0.00001423606,0.0002710475,0.000007268531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973188,0.0005063348,0.0001828797,0.00003207492,0.000007145594,0.00006618986,0.0014661,0.000004180125,0.0004162155],"genre_scores_gemma":[0.9977368,0.0003081151,0.0002095979,0.00006033541,0.00001796069,0.00008374362,0.001455256,0.000004414223,0.0001238328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008017278,"threshold_uncertainty_score":0.0159412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0629164936229469,"score_gpt":0.4622006462622761,"score_spread":0.3992841526393291,"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."}}