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Record W3214722349 · doi:10.3390/pathogens10111471

Demographic, Husbandry, and Biosecurity Factors Associated with the Presence of Campylobacter spp. in Small Poultry Flocks in Ontario, Canada

2021· article· en· W3214722349 on OpenAlexaffabout
Paige M. Schweitzer, Leonardo Susta, Csaba Varga, Marina L. Brash, Michele T. Guerin

Bibliographic record

VenuePathogens · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsMinistry of Agriculture, Food and Rural AffairsUniversity of Guelph
Fundersnot available
KeywordsBiosecurityFlockCampylobacterAnimal husbandryVeterinary medicinePoultry farmingBiologyLogistic regressionOdds ratioTransmission (telecommunications)Environmental healthMedicineEcologyAgriculture

Abstract

fetched live from OpenAlex

This study is part of a 2 year disease surveillance project conducted to establish the prevalence of poultry and zoonotic pathogens, including Campylobacter spp., among small poultry flocks in Ontario, Canada. For each post-mortem submission to the Animal Health Laboratory, a pooled sample of cecal tissue was cultured for Campylobacter spp., and a husbandry and biosecurity questionnaire was completed by the flock owner (n = 153). Using both laboratory and questionnaire data, our objective was to investigate demographic, husbandry, and biosecurity factors associated with the presence of Campylobacter spp. in small flocks. Two multivariable logistic regression models were built. In the farm model, the odds of Campylobacter spp. were higher in turkeys, and when birds were housed in a mixed group with different species and/or types of birds. The odds were lower when antibiotics were used within the last 12 months, and when birds had at least some free-range access. The effect of pest control depended on the number of birds at risk. In the coop model, the odds of Campylobacter spp. were lower when owners wore dedicated clothing when entering the coop. These results can be used to limit the transmission of Campylobacter spp. from small poultry flocks to humans.

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 score0.135
Threshold uncertainty score0.193

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 head0.024
GPT teacher head0.189
Teacher spread0.164 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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