{"id":"W4381386252","doi":"10.1017/s1049023x23004661","title":"A Modified Delphi Study to Improve Prehospital Mass Casualty Incident Response","year":2023,"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":"University of Alberta","funders":"","keywords":"Mass-casualty incident; Triage; Delphi method; Delphi; Advanced life support; Computer science; Medicine; Medical emergency; Poison control; Human factors and ergonomics; Emergency medicine; Artificial intelligence","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":[0.184085,0.001374879,0.001053241,0.003393587,0.006290102,0.004116801,0.003445524,0.002689745,0.009162576],"category_scores_gemma":[0.1905667,0.00127084,0.001829788,0.002401546,0.004953661,0.006753496,0.01219082,0.003910709,0.001801095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009805482,"about_ca_system_score_gemma":0.01968159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003594518,"about_ca_topic_score_gemma":0.004680987,"domain_scores_codex":[0.775756,0.1985303,0.008160725,0.004628576,0.007943474,0.004980924],"domain_scores_gemma":[0.839815,0.1027987,0.005653548,0.008986446,0.03917523,0.003571147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001901289,0.002711327,0.0147639,0.006733297,0.0002157182,0.0009556179,0.7176245,0.002712721,0.004154714,0.02212421,0.02265596,0.2034467],"study_design_scores_gemma":[0.002033355,0.009258323,0.02888518,0.006933628,0.0002614369,0.0006383201,0.7934062,0.01194431,0.005848999,0.02616784,0.1141332,0.0004891041],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7008555,0.00061311,0.09719446,0.01250228,0.001047648,0.1541755,0.001076812,0.0003242531,0.03221043],"genre_scores_gemma":[0.6216196,0.0006884123,0.1325763,0.004937464,0.0001609567,0.234608,0.0005902347,0.000117355,0.004701659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.184085,"threshold_uncertainty_score":0.9735464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05497630043835709,"score_gpt":0.4099484381421916,"score_spread":0.3549721377038345,"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."}}