{"id":"W2900675580","doi":"10.2196/12084","title":"Correlates of Stress in the College Environment Uncovered by the Application of Penalized Generalized Estimating Equations to Mobile Sensing Data","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Drug Abuse; National Institute of Mental Health; National Institutes of Health","keywords":"Stressor; Mobile phone; Computer science; Psychological intervention; Stress (linguistics); Leverage (statistics); Proxy (statistics); Generalized estimating equation; Psychology; Machine learning; Clinical psychology; Telecommunications","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":[0.01525483,0.0007323708,0.0006145086,0.00167067,0.0005075768,0.002128744,0.0008322948,0.0006258726,0.00122611],"category_scores_gemma":[0.07119658,0.0006114842,0.001642173,0.002196659,0.001011548,0.001067705,0.001823604,0.001719241,0.0002137428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007562736,"about_ca_system_score_gemma":0.001604003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01549392,"about_ca_topic_score_gemma":0.01494035,"domain_scores_codex":[0.9885361,0.008626767,0.0005233785,0.001315893,0.0007196949,0.0002782369],"domain_scores_gemma":[0.9496142,0.03832525,0.005658941,0.003794734,0.002262938,0.0003439545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002078305,0.0002625278,0.7980912,0.0003459421,0.001838536,0.0004277146,0.002238947,0.04401427,0.001149355,0.007014365,0.002790907,0.1416184],"study_design_scores_gemma":[0.00002922226,0.0003341062,0.3702759,0.0002262587,0.0003946883,0.0002734523,0.001575919,0.6114561,0.000525547,0.01210408,0.002711418,0.0000931887],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6762713,0.001035731,0.3166666,0.0023417,0.0001179077,0.0004455224,0.0008569189,0.0003731164,0.00189125],"genre_scores_gemma":[0.9438454,0.0004329086,0.05406789,0.0001829693,0.0000756204,0.0002567172,0.0007074806,0.00004208648,0.0003890175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01549392,"threshold_uncertainty_score":0.0806762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08335641223903734,"score_gpt":0.4384330960368869,"score_spread":0.3550766837978496,"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."}}