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Record W4404109734 · doi:10.1017/dmp.2024.204

Public Health Protection Continuity of Operations During the Evacuation and Return to Community Phases of the Unprecedented Evacuation of Two-thirds of the Northwest Territories, Canada, 2023

2024· article· en· W4404109734 on OpenAlexaffabout
Michelle Murti, C. Newberry, Chirag Rohit, Kami Kandola

Bibliographic record

VenueDisaster Medicine and Public Health Preparedness · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsGovernment of Northwest TerritoriesPublic Health Ontario
Fundersnot available
KeywordsPublic healthEnvironmental planningGeographyBusinessEnvironmental healthEnvironmental protectionMedicineNursing

Abstract

fetched live from OpenAlex

Abstract Objective In August 2023, 68% (n=25,900) of the Northwest Territories, Canada, evacuated from wildfires, including the never previously evacuated capital, Yellowknife. Official evacuation orders extended from August 16 to September 6 for this region, impacting health protection services (HPS) in the Territory for remaining residents, and risks on return. Methods The Office of the Chief Public Health Officer (OCPHO) reviewed and implemented priorities over a three-day period prior to the evacuation order for time critical HPS to continue remotely or transfer to receiving jurisdictions. On return to community, OCPHO implemented processes for reviewing surveillance objectives to assess for impacts to affected populations. Results During evacuation, over 15 reports of animal exposures were assessed remotely for rabies prophylaxis. Individuals requiring sexually transmitted infection (STI) follow-up were referred to receiving jurisdictions. One patient with infectious tuberculosis was transferred to another province. Water plant operators were supported with new communication and out-of-Territory testing protocols. On return, enhanced surveillance included: respiratory viruses, STI and blood borne infections, gastrointestinal illness, and toxic drug supplies. Conclusions While some HPS continued to mitigate risks, future surveillance will assess the scale of impacts. Updates to continuity of operations plans need to include considerations for remote and local services.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.048
GPT teacher head0.305
Teacher spread0.257 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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