{"id":"W4361192593","doi":"10.2196/preprints.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 (Preprint)","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"EVERSANA (Canada)","funders":"","keywords":"Medicine; Overweight; Weight loss; Health care; Medical prescription; Obesity; Gerontology; Demography; Family medicine; Nursing; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001043753,0.0002281092,0.0003153287,0.001121504,0.0003652479,0.0007938198,0.0003236169,0.0003064467,0.001287163],"category_scores_gemma":[0.003208174,0.0003392476,0.001346417,0.001843739,0.0002182833,0.0004625125,0.0005737897,0.0004459433,0.0002276013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005710432,"about_ca_system_score_gemma":0.0005273537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01142133,"about_ca_topic_score_gemma":0.009798443,"domain_scores_codex":[0.9988907,0.0003518536,0.000228052,0.0002018992,0.000197135,0.000130303],"domain_scores_gemma":[0.9974149,0.0004585877,0.001424508,0.0001804391,0.0002875568,0.0002339431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00018515,0.00006134138,0.9983084,0.00002922968,0.0001446337,0.00001732273,0.00004386743,0.00002217099,0.00003173254,0.00001102572,0.000110063,0.001034893],"study_design_scores_gemma":[0.0000182065,0.0002874427,0.998855,0.00001804155,0.0001393705,0.00009030021,0.0001900301,0.0001323775,0.00005291993,0.000008483361,0.0002036772,0.000004097922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975412,0.0003598709,0.0001118602,0.00003571825,0.000007694514,0.00003626559,0.001504887,0.000003511314,0.000398927],"genre_scores_gemma":[0.9979609,0.0002595056,0.0001432541,0.00006622692,0.00001639192,0.00005460317,0.001333113,0.000003650775,0.0001622161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01142133,"threshold_uncertainty_score":0.02270967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05789972573254473,"score_gpt":0.4364642052574763,"score_spread":0.3785644795249316,"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."}}