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Record W4416490514 · doi:10.1111/avj.70037

Large‐scale reproductive loss in sheep due to Border disease virus infection, New South Wales, Australia

2025· article· en· W4416490514 on OpenAlexaff
Kate Parrish, ZB Spiers, MS Hazelton, KH Walker, E. Duggan, William D. Graham, Deborah S. Finlaison, Peter D. Kirkland

Bibliographic record

VenueAustralian Veterinary Journal · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsRiverview Hospital
FundersAnimal Health Australia
KeywordsPestivirusSeroprevalenceSerologyTransmission (telecommunications)VirusPregnancyViral diseaseDisease

Abstract

fetched live from OpenAlex

Border disease viruses (BDV) and bovine viral diarrhoea viruses (BVDV) are members of the Pestivirus genus in the family Flaviviridae. While BVDV is one of the most significant endemic viral infections of cattle in Australia, BDV infection is generally considered to be uncommon in Australian sheep. This study describes the widespread detection of BDV on two properties in southern New South Wales following an investigation into poor pregnancy rates, resorbing foetuses and stillborn lambs. Extensive cross-sectional serological studies identified a high seroprevalence in some groups of sheep and low prevalence in others, demonstrating both the extent of infection and the number of susceptible breeding sheep remaining at risk. BDV-specific qRT-PCR confirmed BDV infection of stillborn lambs, and a large number of 'hairy' lambs were confirmed as BDV infected by use of a pestivirus antigen ELISA at marking. In a group of BDV persistently infected lambs that were monitored for 12 months, postweaning survival was low, with 21 of 120 still alive at 5 months of age and 14 still alive at 12 months of age. This study highlights the potential impact BDV can have on production and how management strategies, including breeding young primiparous ewes under intensive management conditions can result in large-scale virus transmission and disease.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.058
GPT teacher head0.333
Teacher spread0.275 · 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.

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 routes1
Has abstractyes

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