{"id":"W4312829686","doi":"10.2196/41162","title":"Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China","year":2022,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Adolescent Sexual and Reproductive Health","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Casual; Logistic regression; Sexual behavior; Reproductive health; Cross-sectional study; Condom; Psychology; Psychological intervention; Demography; Medicine; Clinical psychology; Machine learning; Environmental health; Family medicine; Computer science; Population; Human immunodeficiency virus (HIV)","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":[0.002256655,0.0005269181,0.0007836926,0.001220252,0.0008137518,0.0006408741,0.0006977518,0.0005536595,0.0008588],"category_scores_gemma":[0.003888684,0.000442221,0.001015134,0.00226004,0.0004372796,0.0004190831,0.0008044124,0.0007755303,0.0002174536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493068,"about_ca_system_score_gemma":0.002203968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1515205,"about_ca_topic_score_gemma":0.1317504,"domain_scores_codex":[0.9989609,0.0002652338,0.000126144,0.0002267296,0.0002131004,0.0002080058],"domain_scores_gemma":[0.9967498,0.0007926348,0.0007880349,0.0004789095,0.0006711747,0.0005194544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002524903,0.00003934118,0.9984252,0.000005556158,0.00004955112,0.00001300503,0.00004602228,0.0002493325,0.00003215349,0.000006322336,0.00006961773,0.00103847],"study_design_scores_gemma":[0.00000556215,0.0000368648,0.9964394,0.000005863048,0.00003131819,0.00002037762,0.0002345712,0.003066864,0.00004297517,0.00001567349,0.00009535922,0.000005122734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991239,0.00004437832,0.0001363425,0.00002518127,0.000002577198,0.00001241321,0.0005855609,0.000003686079,0.00006602903],"genre_scores_gemma":[0.9985337,0.0000440652,0.000176054,0.00001265375,0.000003111133,0.00002167469,0.001117985,0.000001613203,0.00008917542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1515205,"threshold_uncertainty_score":0.301277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1775617229302521,"score_gpt":0.4322137149692898,"score_spread":0.2546519920390377,"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."}}