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Record W4407384309 · doi:10.1002/vrc2.70001

<i>Brucella canis</i> in two juvenile labrador retriever littermates with no known travel history

2025· article· en· W4407384309 on OpenAlexaboutno aff
Amy Lord, Oliver Russell, Ombeline McGregor, Robert Dudley, Cassia Hare, Barbara J. Skelly

Bibliographic record

VenueVeterinary Record Case Reports · 2025
Typearticle
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsnot available
Fundersnot available
KeywordsLabrador RetrieverMedicineJuvenileCanisDingoBrucella abortusVeterinary medicineBrucellaBrucellosisPathologyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Two labrador retriever littermates presented separately to investigate chronic lethargy and shifting lameness. In both cases, clinical examination revealed a multi‐limb lameness. Neither the patients nor their dam or sire had a travel history outside the UK. Imaging of the vertebral column in both cases was consistent with discospondylitis. Brucella canis serology demonstrated a rising antibody titre in Case 1 and a strong positive antibody titre in Case 2 (4+/3200), consistent with a diagnosis of B. canis . Due to concerns relating to the poor prognosis, antimicrobial stewardship and zoonotic risk, both patients were euthanased. Since 2020, the UK has seen a rise in cases of B. canis , with most cases having been in imported dogs. This case report highlights how B. canis should be considered in dogs with no travel history and identifies challenges relating to diagnosis and managing these cases in practice.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.048
GPT teacher head0.323
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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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