{"id":"W4360613735","doi":"10.1038/s41746-023-00772-4","title":"Complex modeling with detailed temporal predictors does not improve health records-based suicide risk prediction","year":2023,"lang":"en","type":"article","venue":"npj Digital Medicine","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Food and Drug Administration; Hamilton Health Sciences Foundation; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"Random forest; Logistic regression; Predictive modelling; Machine learning; Ensemble learning; Computer science; Artificial intelligence; Receiver operating characteristic; Artificial neural network; Ensemble forecasting; Regression; Mental health; Statistics; Psychology; Mathematics; Psychiatry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.01331103,0.0008863098,0.00135467,0.0009169548,0.0004553187,0.002131189,0.001042578,0.0007544463,0.002234907],"category_scores_gemma":[0.04541406,0.0005149178,0.001972046,0.001191606,0.0003807981,0.00462726,0.001555954,0.001667728,0.0006144017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007889945,"about_ca_system_score_gemma":0.001447919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01378039,"about_ca_topic_score_gemma":0.02059608,"domain_scores_codex":[0.9952528,0.002995304,0.000418353,0.0006735196,0.0004985519,0.0001614032],"domain_scores_gemma":[0.970093,0.02124511,0.002472759,0.004412228,0.001346103,0.0004309665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00188414,0.000588742,0.5340767,0.0003789865,0.002691226,0.0001333397,0.0005135369,0.2627305,0.001225706,0.002192314,0.003271218,0.1903137],"study_design_scores_gemma":[0.0001097847,0.001136445,0.1227589,0.0002173967,0.0007505958,0.0001759401,0.0002823345,0.8635439,0.0009826525,0.007947687,0.001984431,0.0001099055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.883067,0.001860232,0.1065969,0.001848246,0.0001719857,0.0001971457,0.002183372,0.0009555065,0.003119702],"genre_scores_gemma":[0.9770896,0.0004697061,0.02009935,0.0001989365,0.00006859214,0.00005475155,0.001422584,0.00004879768,0.0005477775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01378039,"threshold_uncertainty_score":0.0703963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05809156678828752,"score_gpt":0.325537554484045,"score_spread":0.2674459876957574,"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."}}