{"id":"W4313242404","doi":"10.2196/42420","title":"Prediction of Mental Health Problem Using Annual Student Health Survey: Machine Learning Approach","year":2022,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Mental Health via Writing","field":"Psychology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hokkaido University; Keio University; Kanazawa University","keywords":"Mental health; Logistic regression; Random forest; Statistics; Demographics; Computer science; Psychology; Artificial intelligence; Machine learning; Mathematics; Demography; Psychiatry; Sociology","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.009534618,0.0004656371,0.001062524,0.0004284498,0.003380703,0.0000243689,0.0004593608,0.00008997589,0.0006252379],"category_scores_gemma":[0.000007272501,0.0005347311,0.0001480816,0.0009099524,0.0001180929,0.000188098,0.0005824594,0.001602533,0.00001826706],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005626304,"about_ca_system_score_gemma":0.001135793,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03508936,"about_ca_topic_score_gemma":0.0007481585,"domain_scores_codex":[0.9863905,0.007028932,0.002281069,0.001097322,0.001463912,0.001738276],"domain_scores_gemma":[0.9965507,0.0001015384,0.001988336,0.0004968327,0.0000535742,0.0008090662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002692854,0.01417552,0.4986642,0.004302348,0.0003429921,0.0000101744,0.3484768,0.001137119,0.0001395051,0.001313999,0.05781491,0.07092957],"study_design_scores_gemma":[0.01633615,0.02683449,0.6415327,0.0008319566,0.00001647159,0.001160529,0.2719747,0.01090657,0.00002088766,0.00004295263,0.02908744,0.001255202],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9616722,0.008040042,0.0002874307,0.004102831,0.002507095,0.009776624,0.01209863,0.0003806418,0.00113443],"genre_scores_gemma":[0.985348,0.0001804619,0.002542345,0.003391484,0.000186116,0.0005305989,0.00676155,0.0001480619,0.0009114147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1428685,"threshold_uncertainty_score":0.9997104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08069304746853954,"score_gpt":0.4254248372285154,"score_spread":0.3447317897599759,"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."}}