{"id":"W4232780045","doi":"10.2196/preprints.25288","title":"Information and Communication Technology Use in Suicide Prevention: Scoping Review (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Institut universitaire en santé mentale de Montréal; Quebec Network for Research on Aging; Université de Montréal; Institut Universitaire en Santé Mentale de Québec; Université du Québec à Montréal; Université de Sherbrooke","funders":"","keywords":"PsycINFO; Information and Communications Technology; Suicide prevention; Preprint; Grey literature; Poison control; Occupational safety and health; Best practice; Injury prevention; Medicine; Human factors and ergonomics; Psychology; MEDLINE; Computer science; Medical emergency; World Wide Web; Political science","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":[0.01227651,0.001330809,0.003895646,0.01771963,0.001567733,0.005137749,0.001583182,0.003500691,0.008554313],"category_scores_gemma":[0.0677148,0.001197436,0.003968291,0.020792,0.001226121,0.005000097,0.002534043,0.001983885,0.001258102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005159094,"about_ca_system_score_gemma":0.02103643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008525906,"about_ca_topic_score_gemma":0.0171111,"domain_scores_codex":[0.9881705,0.003808385,0.004775619,0.0006420474,0.002278192,0.0003252736],"domain_scores_gemma":[0.9415838,0.04290877,0.00687505,0.000741526,0.007436318,0.0004546256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001116241,0.00004727329,0.0009399059,0.810211,0.001100539,0.0001512848,0.001050104,0.0001478068,0.0002057206,0.00117501,0.0198021,0.1650577],"study_design_scores_gemma":[0.00002063344,0.00006058645,0.001873153,0.9496765,0.002287303,0.0002046209,0.0006563577,0.00005865484,0.000134414,0.0003530125,0.04465769,0.00001710041],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005029421,0.9959034,0.0001774717,0.001062427,0.0007265059,0.0003627059,0.0002515907,0.000008170352,0.001004705],"genre_scores_gemma":[0.003337782,0.9941489,0.0004968089,0.0005767593,0.0003023296,0.0006668392,0.0002048016,0.000006359418,0.0002594845],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01771963,"threshold_uncertainty_score":0.06492519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09943677424619404,"score_gpt":0.3916331027130958,"score_spread":0.2921963284669017,"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."}}