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Record W3005866368 · doi:10.3390/ani10020283

Control and Surveillance Operations to Prevent Chronic Wasting Disease Establishment in Free-Ranging White-Tailed Deer in Québec, Canada

2020· article· en· W3005866368 on OpenAlexaffabout
Marianne Gagnier, Isabelle Laurion, Anthony J. DeNicola

Bibliographic record

VenueAnimals · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsMinistère des Ressources naturelles et des Forêts
Fundersnot available
KeywordsChronic wasting diseaseOdocoileusCervus elaphusPopulationVeterinary medicineBiologyWildlifeGeographyMedicineDiseaseEcologyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Chronic wasting disease (CWD), a degenerative and fatal prion disease affecting cervids, was detected for the first time in the province of Québec, Canada, in a red deer (Cervus elaphus) farm in the Laurentides region on 10 September 2018. To assess CWD prevalence and control the disease in the free-ranging white-tailed deer (Odocoileus virginianus) population, a response plan including enhanced surveillance, population control, regulatory measures, and public outreach was deployed by the Ministry of Forests, Wildlife, and Parks (MFFP). In the 401 km2 white-tailed deer control area, a total of 750 free-ranging white-tailed deer were culled over 70 days, from 22 September to 15 December 2018. Of the culled deer, 534 were tested for CWD. We also tested for CWD a total of 447 white-tailed deer hunted from the enhanced surveillance zone and 2584 free-ranging white-tailed deer harvested outside this zone. Regulations were applied to prevent the spread of the disease through movements of infected animals harvested by hunters. Although no case of CWD was detected in free-ranging cervids in Québec in 2018, this does not confirm the absence of the disease in these populations. However, the results suggest that if CWD is present, few free-ranging cervids are infected, making it possible to prevent its establishment in the province of Québec.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.965

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)0.0000.000

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 head0.005
GPT teacher head0.214
Teacher spread0.208 · 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 teacher head, 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

Citations16
Published2020
Admission routes2
Has abstractyes

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