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Genetic structure and rabies spread potential in raccoons: the role of landscape barriers and sex‐biased dispersal

2012· article· en· W1539923065 on OpenAlexafffundabout
Héloïse Côté, Dany Garant, Karine Robert, Julien Mainguy, Fanie Pelletier

Bibliographic record

VenueEvolutionary Applications · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)Ministère des Ressources naturelles et des ForêtsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsBiologyBiological dispersalRabiesEcologyZoologyEvolutionary biologyDemographyVirologyPopulation

Abstract

fetched live from OpenAlex

Identifying natural barriers to movements of hosts associated with infectious diseases is essential for developing effective control strategies. Raccoon rabies variant (RRV) is a zoonosis of concern for humans because its main vector, the raccoon (Procyon lotor), is found near residential areas. In Québec, Canada, all cases of RRV found in raccoons since 2006 were detected on the eastern side of the Richelieu River, suggesting that this river acts as a barrier to gene flow and thus the potential for RRV to spread. The objectives of this study were to characterize the genetic structure of raccoon populations and assess the effect of the Richelieu River on the population structure in southern Québec, Canada. We also evaluated whether RRV spread potential differed between sex and at a larger spatial scale. Our analyses revealed a weak signal of genetic differentiation among individuals located on each side of the Richelieu River. At a larger spatial scale, genetic structuring was weak. Our results suggest that rivers might not always efficiently restrain raccoon movements and spread of RRV. We suggest that the difference in genetic structure found between sexes can be partly explained by male movements during the breeding season in winter, when ice bridges allow passage over most rivers in 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 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)0.000
metaresearch head score (Gemma)0.001
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 score0.470
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.203
Teacher spread0.200 · 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

Citations47
Published2012
Admission routes3
Has abstractyes

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