{"id":"W4409281783","doi":"10.1016/j.biopsych.2025.02.866","title":"627. Understanding the Biopsychosocial Mechanisms of Risk for Suicide Using Machine Learning and a Resilience Framework","year":2025,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Resilience and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Biopsychosocial model; Resilience (materials science); Psychology; Psychotherapist; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009994035,0.0003477994,0.0002455389,0.001179076,0.0005682398,0.001260331,0.0004062963,0.0007572165,0.004433517],"category_scores_gemma":[0.003113331,0.0001139736,0.0004007145,0.0005305181,0.001355841,0.001981814,0.0007976773,0.001220134,0.0005097895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008052376,"about_ca_system_score_gemma":0.001116608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005271746,"about_ca_topic_score_gemma":0.00739047,"domain_scores_codex":[0.9998355,0.00006848319,0.000008385877,0.0000255086,0.00003930934,0.00002283375],"domain_scores_gemma":[0.9992149,0.0004707295,0.00008997122,0.0000464826,0.0001069204,0.00007099751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00009365237,0.0003043762,0.1036696,0.0004562196,0.0002582244,0.0005292348,0.002135197,0.01250737,0.002498441,0.4208028,0.0130593,0.4436856],"study_design_scores_gemma":[0.0000194483,0.0001301087,0.1064092,0.0008383026,0.00009023403,0.0006097923,0.001797606,0.04905316,0.001045866,0.8154525,0.02449714,0.00005671506],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3729325,0.03688287,0.2322498,0.2190449,0.001234193,0.000240147,0.001308529,0.000399918,0.1357071],"genre_scores_gemma":[0.9559858,0.01037022,0.02125035,0.002806683,0.0003818749,0.00006292436,0.0002369,0.00001524609,0.008890016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005271746,"threshold_uncertainty_score":0.0148316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06477963565263238,"score_gpt":0.4143572822473701,"score_spread":0.3495776465947377,"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."}}