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Record W2146530820 · doi:10.1139/cjz-2013-0186

Seasonal variation in foraging behaviour of plains zebra (<i>Equus</i> <i>quagga</i>) may alter contact with the anthrax bacterium (<i>Bacillus</i> <i>anthracis</i>)

2014· article· en· W2146530820 on OpenAlexvenueno aff
Zepee Havarua, Wendy C. Turner, John K. E. Mfune

Bibliographic record

VenueCanadian Journal of Zoology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsnot available
Fundersnot available
KeywordsForagingBiologySeasonalityBacillus anthracisEquusDry seasonEcologyWet seasonHerbivoreZoologyVeterinary medicineBacteria

Abstract

fetched live from OpenAlex

Pathogens transmitted via the environment are often aggregated in space, and seasonal variation in wildlife foraging behaviour may alter contact rates with environmental pathogens. The soil-borne bacterium Bacillus anthracis Cohn, 1872 causes anthrax, and herbivores acquire gastrointestinal anthrax by ingesting spores. Therefore host foraging behaviour could be a fundamental component of anthrax epidemiology. This study investigated seasonal changes in bite density and diet of plains zebras (Equus quagga Boddaert, 1785) in relation to anthrax seasonality in Etosha National Park, Namibia, where most zebra anthrax cases are observed in wet seasons. The diet of zebras shifted from more short grasses during the wet season to more tall grasses in the dry season, suggesting a greater potential for soil ingestion in wet seasons. Zebras also foraged most intensively in the wet season with the number of bites/step declining through the dry season. This higher bite density in wet seasons may lead individuals to ingest greater concentrations of the pathogen if foraging in a localized infectious area. Although sex and reproductive state affected bite density, no sex difference in anthrax occurrence was observed. This study demonstrates how considering variation in host foraging behaviour may enhance our understanding of disease seasonality for pathogens with foraging-dependent transmission.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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

Citations32
Published2014
Admission routes1
Has abstractyes

Explore more

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