{"id":"W2921616123","doi":"10.1001/jamapsychiatry.2019.0174","title":"Prediction Models for Suicide Attempts and Deaths","year":2019,"lang":"en","type":"review","venue":"JAMA Psychiatry","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":524,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"PsycINFO; Poison control; Veterans Affairs; Predictive modelling; MEDLINE; Cochrane Library; Predictive validity; Population; Medicine; Suicide prevention; Injury prevention; Suicide attempt; Psychiatry; Meta-analysis; Clinical psychology; Medical emergency; Machine learning; Computer science; Environmental health; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003623619,0.0005882003,0.001697529,0.0002562418,0.0001710644,0.0000725431,0.0002995493,0.0008516508,0.0001240796],"category_scores_gemma":[0.00002514097,0.0004864629,0.0006288903,0.0001858109,0.00005430847,0.0001531078,0.0000923759,0.0005089502,0.0003333223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000533766,"about_ca_system_score_gemma":0.0001554048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006484827,"about_ca_topic_score_gemma":0.00003212375,"domain_scores_codex":[0.9974229,0.0001543292,0.0007782175,0.0009250412,0.0001860312,0.0005334616],"domain_scores_gemma":[0.998274,0.0004036466,0.0004057131,0.0007305274,0.00007604394,0.0001101297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009817884,0.000148197,0.001259656,0.01637142,0.00163849,0.0000031844,0.0004112305,0.000001547236,2.61625e-8,0.01439517,0.2043756,0.7612973],"study_design_scores_gemma":[0.001262679,0.0002050407,0.0002635704,0.001623008,0.002072924,0.00008061658,0.0002314678,0.00003032596,1.185261e-8,0.003958118,0.9897798,0.0004923855],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003566098,0.9734639,0.0005184548,0.0003063118,0.007821973,0.002058401,0.0005881194,0.0001514531,0.01505575],"genre_scores_gemma":[0.00001611809,0.990733,0.0008611264,0.000600645,0.002019012,0.0008901461,0.0002583353,0.000138871,0.004482701],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7854043,"threshold_uncertainty_score":0.9997587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.130834958258833,"score_gpt":0.382674556490706,"score_spread":0.251839598231873,"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."}}