MétaCan
Menu
Back to cohort
Record W2049166903 · doi:10.1017/s1049023x12001446

Triage During Mass Gatherings

2012· article· en· W2049166903 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePrehospital and Disaster Medicine · 2012
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of British Columbia
FundersU.S. National Library of Medicine
KeywordsTriageMass-casualty incidentMass gatheringMedical emergencyPopulationMedicinePoison controlPresentation (obstetrics)Injury preventionNursingPublic healthSurgeryEnvironmental health

Abstract

fetched live from OpenAlex

Triage is a complex process and is one means for determining which patients most need access to limited resources. Triage has been studied extensively, particularly in relation to triage in overcrowded emergency departments, where individuals presenting for treatment often are competing for the available stretchers. Research also has been done in relation to the use of prehospital and field triage during mass-casualty incidents and disasters. In contrast, scant research has been done to develop and test an effective triage approach for use in mass-gathering and mass-participation events, although there is a growing body of knowledge regarding the health needs of persons attending large events. Existing triage and acuity scoring systems are suboptimal for this unique population, as these events can involve high patient presentation rates (PPR) and, occasionally, critically ill patients. Mass-gathering events are dangerous; a higher incidence of injury occurs than would be expected from general population statistics. The need for an effective triage and acuity scoring system for use during mass gatherings is clear, as these events not only create multiple patient encounters, but also have the potential to become mass-casualty incidents. Furthermore, triage during a large-scale disaster or mass-casualty incident requires that multiple, local agencies work together, necessitating a common language for triage and acuity scoring. In reviewing existing literature with regard to triage systems that might be employed for this population, it is noted that existing systems are biased toward traumatic injuries, usually ignoring mitigating factors such as alcohol and drug use and environmental exposures. Moreover, there is a substantial amount of over-triage that occurs with existing prehospital triage systems, which may lead to misallocation of limited resources. This manuscript presents a review of the available literature and proposes a triage system for use during mass gatherings that also may be used in the setting of mass-casualty incidents or disaster responses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.380
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it