{"id":"W4405048805","doi":"10.2196/49927","title":"Machine Learning–Based Suicide Risk Prediction Model for Suicidal Trajectory on Social Media Following Suicidal Mentions: Independent Algorithm Validation","year":2024,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Mental Health via Writing","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Ottawa Hospital; Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Ontario Society of Occupational Therapists; Mach-Gaensslen Foundation of Canada; Ottawa Hospital Research Institute; Ontario Medical Association; University of Ottawa","keywords":"Suicidal ideation; Cohort; Social media; Machine learning; Poison control; Suicide prevention; Suicide attempt; Psychology; Artificial intelligence; Timeline; Computer science; Medicine; Algorithm; Medical emergency; Statistics; World Wide Web; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01448902,0.001178208,0.001432573,0.002153153,0.0007953816,0.001482714,0.001779677,0.001489641,0.002429718],"category_scores_gemma":[0.01982021,0.0004347654,0.001693433,0.000821157,0.0005389096,0.0009109218,0.001315378,0.002779065,0.0009242592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536541,"about_ca_system_score_gemma":0.002603157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01466,"about_ca_topic_score_gemma":0.008225786,"domain_scores_codex":[0.9977967,0.00123274,0.0002069421,0.0004219442,0.0001896856,0.0001520077],"domain_scores_gemma":[0.9842088,0.01137317,0.0007708506,0.0007596455,0.002553938,0.0003336895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001827267,0.002326506,0.3126737,0.0001927579,0.001098256,0.0002492017,0.000326465,0.4790192,0.0010894,0.001143262,0.004556726,0.1954972],"study_design_scores_gemma":[0.00004362109,0.0001462313,0.005690556,0.00002267141,0.00004690087,0.00003159824,0.00004541338,0.9931766,0.0002607517,0.000376253,0.0001483463,0.00001102354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8518822,0.0008844649,0.1390798,0.001466778,0.000192326,0.001076362,0.001658751,0.001542711,0.002216561],"genre_scores_gemma":[0.94389,0.0001583947,0.05159613,0.0002017251,0.00005657257,0.0007612048,0.002149348,0.00003461614,0.001151974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01466,"threshold_uncertainty_score":0.07662618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1566295403954365,"score_gpt":0.4881557959797446,"score_spread":0.331526255584308,"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."}}