{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001445658,0.0002777591,0.0004663737,0.002170034,0.0004356131,0.0006229084,0.000507645,0.0004811741,0.002276803],"category_scores_gemma":[0.004238875,0.0003958887,0.001070634,0.002158941,0.0001785532,0.0004199651,0.0006006586,0.0009270603,0.0004572972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004120786,"about_ca_system_score_gemma":0.0006861214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01392374,"about_ca_topic_score_gemma":0.01462574,"domain_scores_codex":[0.9989322,0.0003155499,0.0001938496,0.0002234815,0.0002030233,0.0001319206],"domain_scores_gemma":[0.9950563,0.0008573642,0.002038494,0.0003867277,0.001112494,0.0005486312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008585296,0.00007010269,0.9989045,0.0000181192,0.00008380022,0.00001290444,0.00003135551,0.00002206767,0.00005547304,0.000008153646,0.0001917156,0.000515979],"study_design_scores_gemma":[0.00001510491,0.0001258039,0.9992618,0.00001032769,0.00005234286,0.00006768129,0.00008454031,0.0001437595,0.00004516262,0.000007556131,0.0001831546,0.000002681852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901591,0.0001692723,0.0002465713,0.00003361964,0.000007152372,0.0001414794,0.008571642,0.00001230525,0.0006587864],"genre_scores_gemma":[0.9884844,0.0001778439,0.0005581603,0.00006326136,0.00001556057,0.0003891807,0.009832572,0.000009814612,0.0004691844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01392374,"threshold_uncertainty_score":0.0276854,"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."}}