{"id":"W4320857997","doi":"10.1017/dmp.2022.287","title":"A Scoping Review of Pediatric Mass-Casualty Incident Triage Algorithms","year":2023,"lang":"en","type":"review","venue":"Disaster Medicine and Public Health Preparedness","topic":"Disaster Response and Management","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Montreal Children's Hospital","funders":"","keywords":"Triage; CINAHL; Medicine; Mass-casualty incident; Population; MEDLINE; Medical emergency; Algorithm; Scopus; Poison control; Injury prevention; Nursing; Computer science; Environmental health; Psychological intervention","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01178526,0.0008095478,0.00574453,0.001119047,0.0004903433,0.00002272064,0.0007206819,0.0004307077,0.0007876491],"category_scores_gemma":[0.002726634,0.0005717878,0.0003733341,0.001922238,0.0001806766,0.0002612827,0.0008243155,0.001017961,0.0002335763],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004103751,"about_ca_system_score_gemma":0.006514763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004387502,"about_ca_topic_score_gemma":0.0001155106,"domain_scores_codex":[0.9858038,0.005186626,0.005242352,0.001113636,0.001113415,0.001540151],"domain_scores_gemma":[0.9912918,0.002415745,0.003546943,0.001349365,0.0003436789,0.001052476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008341572,0.00004734665,0.000007996505,0.6759002,0.0001181974,0.00001548778,0.02519355,5.002251e-9,1.983938e-9,0.0001423065,0.03927965,0.2592869],"study_design_scores_gemma":[0.0005762957,0.0001606381,0.000001411288,0.4721696,0.0004481498,0.000004153262,0.01435885,0.000001349985,2.134398e-10,0.00002169404,0.5120146,0.0002432049],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002267661,0.9794397,0.0004878446,0.00159502,0.00221786,0.01220756,0.0001729519,0.0002144026,0.003642037],"genre_scores_gemma":[0.000001193607,0.9858377,0.00006066658,0.006108559,0.001736143,0.003363104,0.0007032501,0.0001508957,0.002038493],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.472735,"threshold_uncertainty_score":0.9996734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4670619511705946,"score_gpt":0.5776299986283402,"score_spread":0.1105680474577456,"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."}}