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Record W2100785440 · doi:10.1017/s148180350000806x

Canadian emergency department preparedness for a nuclear, biological or chemical event

2003· article· en· W2100785440 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2003
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsMcMaster UniversityHamilton Health SciencesHealth Sciences Centre
Fundersnot available
KeywordsPreparednessTerrorismMedical emergencyMedicineMass CasualtyEvent (particle physics)AccidentalChemical warfareChemical agentsBiological warfareEnvironmental healthToxicologyPolitical scienceEngineeringLawBiology

Abstract

fetched live from OpenAlex

Since the terror attacks of September 11th, emergency departments across North America have become more aware of the need to be prepared to deal with a mass casualty terror event, particularly one involving nuclear, biological or chemical contaminants. The effects of such an attack could also be mimicked by accidental release of toxic chemicals, radioactive substances or biological agents unrelated to terrorist activity. The purpose of this study was to review the risks and characteristics of these events and to assess the preparedness of Canadian emergency departments to respond. This was done by means of a survey, which showed a significant risk of a mass casualty event (most likely chemical) coupled with a deficiency in preparedness -- most notably in the availability of appropriate equipment, antidotal therapy and decontamination capability. There were also significant deficiencies in the ability to respond to a major biologic or nuclear event.

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0570.000

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 head0.196
GPT teacher head0.448
Teacher spread0.252 · 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