{"id":"W4396575673","doi":"10.3390/healthcare12090909","title":"Hazard Flagging as a Risk Mitigation Strategy for Violence against Emergency Medical Services","year":2024,"lang":"en","type":"article","venue":"Healthcare","topic":"Workplace Violence and Bullying","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Windsor; Western University; University of Toronto","funders":"University of Windsor","keywords":"Flagging; Hazard; Medical emergency; Attendance; Incident report; Medicine; Occupational safety and health; Poison control; Injury prevention; Suicide prevention; Harm; Emergency department; Computer security; Emergency medicine; Psychology; Psychiatry; Computer science; Geography; Political science; Social psychology","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":[0.01217621,0.0004358742,0.000268173,0.003033477,0.0008203208,0.00109606,0.0008374295,0.0004964141,0.001807547],"category_scores_gemma":[0.0361596,0.0002879762,0.0005036326,0.000821905,0.0004848292,0.001408715,0.001261326,0.0006711675,0.0002520178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007812406,"about_ca_system_score_gemma":0.003201503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002606028,"about_ca_topic_score_gemma":0.006178398,"domain_scores_codex":[0.9912155,0.00645982,0.000605715,0.0002876531,0.001118682,0.0003127467],"domain_scores_gemma":[0.9709592,0.01475024,0.01004999,0.001125526,0.002236911,0.0008780505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004542776,0.001715697,0.5082706,0.001023804,0.0001424649,0.0003887496,0.003464986,0.001599092,0.002132008,0.0008445402,0.003329853,0.4766338],"study_design_scores_gemma":[0.0002501936,0.01143648,0.9214721,0.002909559,0.0004596304,0.003215359,0.01263153,0.01970378,0.00735314,0.002289342,0.01804107,0.0002378186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548872,0.002728323,0.02611237,0.003896721,0.0002010196,0.002743241,0.0003078558,0.000580131,0.008543067],"genre_scores_gemma":[0.9664177,0.00092836,0.03135783,0.000374745,0.0000694921,0.0003054717,0.0001169341,0.00001064908,0.000418934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01217621,"threshold_uncertainty_score":0.06439465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02556213469528025,"score_gpt":0.3831886542383712,"score_spread":0.3576265195430909,"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."}}