{"id":"W4383301655","doi":"10.2196/44920","title":"Prospective Association Between Video and Computer Game Use During Adolescence and Incidence of Metabolic Health Risks: Secondary Data Analysis","year":2023,"lang":"en","type":"article","venue":"JMIR Pediatrics and Parenting","topic":"Impact of Technology on Adolescents","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Mental Health","keywords":"Video game; Obesity; Computer game; Association (psychology); Medicine; Quartile; Diabetes mellitus; Metabolic syndrome; Body mass index; Gerontology; Psychology; Multimedia; Internal medicine; Computer science; Endocrinology; Confidence interval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001566695,0.0001093852,0.0003496172,0.0003701408,0.0004693728,0.0001745228,0.0002094165,0.000120813,0.000002969674],"category_scores_gemma":[0.0005357901,0.0001170983,0.00002999039,0.001446023,0.000116056,0.0005602135,0.0005072404,0.0002444147,0.000001298471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004471811,"about_ca_system_score_gemma":0.00009698215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002379727,"about_ca_topic_score_gemma":0.0007964982,"domain_scores_codex":[0.9984315,0.000160155,0.0003152648,0.000392265,0.0003416715,0.0003591587],"domain_scores_gemma":[0.9987969,0.0002652852,0.0005180204,0.0002105329,0.00008768593,0.0001216001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002555574,0.00001163352,0.992508,0.00008784556,0.00006923376,0.000001151423,0.002053002,0.000002642853,0.000002834471,0.00003862574,0.00009013512,0.00513233],"study_design_scores_gemma":[0.0002130658,0.00001333103,0.9982527,0.00003093193,0.0001657386,2.796063e-7,0.0004576061,0.0005964747,0.000005841979,0.00009749527,0.00005889821,0.0001076411],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998314,0.0007223857,0.0001415461,0.000252084,0.00005934292,0.0002778192,0.0001394704,0.0000825282,0.00001077605],"genre_scores_gemma":[0.9960401,0.003350417,0.0002948079,0.00002798292,0.0002014,0.000004055481,0.00003063499,0.000007213519,0.00004341185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005744685,"threshold_uncertainty_score":0.477513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0494161165057032,"score_gpt":0.3586399079415621,"score_spread":0.3092237914358589,"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."}}