{"id":"W2605578836","doi":"10.1017/s1049023x17005301","title":"A Public Health Emergency Simulation Tool for Enhanced Training in Emergency Preparedness and Response","year":2017,"lang":"en","type":"article","venue":"Prehospital and Disaster Medicine","topic":"Disaster Response and Management","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; Queen's University","funders":"","keywords":"Emergency response; Training (meteorology); Emergency management; Preparedness; Simulation training; Medical emergency; Action (physics); Computer science; Engineering; Medicine; Simulation; 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":[0.002338808,0.001185757,0.0004788358,0.001168648,0.0004186526,0.001326039,0.001337394,0.0007915244,0.02482639],"category_scores_gemma":[0.01060818,0.0003996704,0.001098942,0.0004916638,0.0002317313,0.001465298,0.002399641,0.001140221,0.005786344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003974569,"about_ca_system_score_gemma":0.00122236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006819073,"about_ca_topic_score_gemma":0.001430893,"domain_scores_codex":[0.998901,0.0005881272,0.00008046243,0.0001433296,0.0001716763,0.0001153288],"domain_scores_gemma":[0.9961162,0.002098297,0.0003379359,0.00027427,0.000336957,0.0008363627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004984367,0.02020559,0.1533805,0.002894499,0.0004137798,0.001660018,0.004481267,0.02373835,0.01207328,0.002991363,0.09015453,0.6830225],"study_design_scores_gemma":[0.003180353,0.02074548,0.3934366,0.004496006,0.001160054,0.00576827,0.007553103,0.2687847,0.01968895,0.01073957,0.2635809,0.0008660161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8272287,0.0008047846,0.09852874,0.002633032,0.0007489322,0.005425446,0.01121605,0.017421,0.03599323],"genre_scores_gemma":[0.7983279,0.0009333633,0.1728805,0.0007367713,0.0002140033,0.003502395,0.008732375,0.0003927618,0.01427992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02482639,"threshold_uncertainty_score":0.08305252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.196281829874794,"score_gpt":0.4618992717742399,"score_spread":0.2656174418994459,"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."}}