{"id":"W2942513590","doi":"10.1017/cem.2019.326","title":"P135: TriagED: A serious game for mass casualty triage and field disaster management","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Disaster Response and Management","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Triage; Usability; Mass-casualty incident; Medicine; Medical emergency; Emergency medical services; Computer science; Poison control; Human factors and ergonomics","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":[0.001576068,0.001156238,0.0003305505,0.0005682587,0.003242758,0.002778989,0.00170156,0.002867865,0.1361804],"category_scores_gemma":[0.004977312,0.0002925932,0.0007084889,0.0002487131,0.0009910869,0.002382125,0.004114737,0.003206436,0.02410483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221558,"about_ca_system_score_gemma":0.002921941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005056972,"about_ca_topic_score_gemma":0.02950786,"domain_scores_codex":[0.9991654,0.0002759773,0.00002963444,0.00007299781,0.0002397982,0.0002161458],"domain_scores_gemma":[0.9971011,0.0003781399,0.00006861378,0.00005532787,0.0003404127,0.002056402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005298976,0.0006749461,0.002079339,0.0002090134,0.00001428102,0.0006142692,0.001590428,0.0004587575,0.002114626,0.005843969,0.8892649,0.09660556],"study_design_scores_gemma":[0.0002588829,0.00128781,0.007046327,0.0003050383,0.00002645172,0.001254723,0.005025329,0.004866268,0.001245412,0.01354585,0.9650335,0.0001043895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08018778,0.001270952,0.06117602,0.14411,0.03670542,0.003085624,0.004529397,0.01011124,0.6588235],"genre_scores_gemma":[0.3088175,0.001372137,0.1183484,0.0312605,0.005822429,0.003073857,0.004042475,0.001564067,0.5256985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1361804,"threshold_uncertainty_score":0.4555689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1219360320536068,"score_gpt":0.4415131204214237,"score_spread":0.3195770883678168,"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."}}