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Record W4415015816 · doi:10.3168/jds.2025-27122

The effect of bovine leukemia virus infection on health and growth of nonreplacement dairy calves

2025· article· en· W4415015816 on OpenAlexafffundabout
Kendra Broadfoot, Frank van der Meer, Rita Couto Serrenho, Francesca Pharo, A.J. Keunen, D.L. Renaud

Bibliographic record

VenueJournal of Dairy Science · 2025
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of CalgaryUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaDairy Farmers of OntarioDairy Farmers of CanadaUniversity of Guelph
KeywordsBovine respiratory diseaseDiarrheaPoisson regressionRespiratory systemBovine leukemia virusProportional hazards modelDairy cattleFeces

Abstract

fetched live from OpenAlex

The objective of this cohort study was to determine if bovine leukemia virus (BLV) positivity, identified using quantitative PCR (qPCR), was associated with health and growth outcomes in nonreplacement dairy calves. A commercial calf-raising facility located in Southwestern Ontario was used, where a total of 768 male dairy calves (726 Holstein, 42 crossbred), estimated to be 3 to 10 d of age, had 3 blood samples taken at 1 d, 30, and 84 after arrival to the facility. Whole blood EDTA samples were taken and sent to the University of Calgary Faculty of Veterinary Medicine for qPCR analysis to determine positivity for BLV. Calves were determined to be positive using a baseline threshold of >200 relative fluorescence unit by <40 cycles. All calves were health scored 2 times daily for fecal consistency and respiratory disease, using the UC Davis respiratory scoring chart. Additionally, calves were weighed at time of arrival and weekly thereafter until they left the facility at 84 d. Mixed linear regression models were built to assess ADG (kg/d) over 84 d and feed efficiency (ME/kg of gain), whereas a Poisson model was built to assess the number of observations with a respiratory score of ≥5. Further, a negative binomial model was built to assess the number of observations with diarrhea (score of ≥2), and a zero-truncated Poisson model was built to assess the number of observations with no clinical signs of respiratory disease (e.g., respiratory score of 0). Treatment for respiratory disease and diarrhea was also analyzed using a Cox proportional hazard model. Two calves had incomplete blood sampling and were therefore removed from the analysis, leaving a total of 766 calves. A total of 43 (5.9%) calves tested positive for BLV via qPCR testing over the 84-d period. Calves that were BLV-positive were associated with a greater number of observations with a respiratory score of ≥5 (incidence rate ratio [IRR] = 1.91, 95% CI: 1.69 to 2.17) and a lower number of observations with a score of 0 (IRR = 0.98, 95% CI: 0.95 to 1.00). There was no difference identified between BLV positivity and ADG (kg/d), feed efficiency (ME/kg of gain), or diarrhea. Overall, this study identifies an association between BLV status and respiratory disease occurrence in preweaning calves. Although the underlying mechanisms and long-term effects remain unclear, these findings highlight the need for further research to determine whether BLV plays a causal role in respiratory disease in calves.

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)0.002
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.354
Teacher spread0.331 · 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
Published2025
Admission routes3
Has abstractyes

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