{"id":"W2802153593","doi":"10.2196/10144","title":"Using Neural Networks with Routine Health Records to Identify Suicide Risk: Feasibility Study","year":2018,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Health and Care Research Wales","keywords":"Mental health; Suicide prevention; Medicine; Occupational safety and health; Psychiatry; Medical prescription; Poison control; Medical record; Medical emergency; Psychology; Nursing","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":[0.009569142,0.0007061922,0.0005283665,0.001410365,0.00036094,0.0006525441,0.001008083,0.000950394,0.000979724],"category_scores_gemma":[0.02654984,0.0004037971,0.0006317415,0.0008599771,0.0004779188,0.001241516,0.001150911,0.0006590108,0.0003734131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009854988,"about_ca_system_score_gemma":0.0009681286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01308265,"about_ca_topic_score_gemma":0.008517997,"domain_scores_codex":[0.9945754,0.003849888,0.0003282031,0.0004868123,0.0005041313,0.0002556236],"domain_scores_gemma":[0.9857627,0.008995312,0.001135098,0.001624691,0.002002149,0.0004801069],"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":[0.003743203,0.006073136,0.8744862,0.0001681749,0.0004275969,0.0003641764,0.0006494214,0.03144364,0.001533385,0.000212192,0.0005076976,0.08039112],"study_design_scores_gemma":[0.0004589628,0.009507097,0.3837827,0.00006754,0.00025293,0.0005352832,0.001039412,0.6006578,0.002291797,0.0006816571,0.0006535737,0.00007126092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953565,0.00003604663,0.003562248,0.00007225457,0.000008788718,0.0003625496,0.0002379169,0.00002842745,0.0003351536],"genre_scores_gemma":[0.9906781,0.00004000555,0.008181886,0.00003089828,0.00001408646,0.0002921435,0.0005853933,0.000002761078,0.0001748624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01308265,"threshold_uncertainty_score":0.05060703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1112987353383242,"score_gpt":0.4754204588302163,"score_spread":0.3641217234918921,"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."}}