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Assessment of the evolution of the proportion of respiratory and enteric pathogens and diseases in pre-weaned unvaccinated dairy heifers from Québec, Canada

2021· article· en· W4324270515 on OpenAlexafffundabout
J. Denis-Robichaud, Marie-Ève Tremblay Cléroux, Sébastien Buczinski, Marie-Lou Gauthier, J. Dubuc, David Francoz

Bibliographic record

VenueThe Bovine Practitioner · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversité de MontréalMinistère de l'Agriculture, des Pêcheries et de l'AlimentationService de Recherche et d'EXpertise en Transformation des Produits ForestiersUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaZoetis
KeywordsDiarrheaRespiratory systemMedicineBovine respiratory diseaseFecesVeterinary medicineLungInternal medicineBiologyImmunologyMicrobiology

Abstract

fetched live from OpenAlex

The objective of this study was to describe the proportion of enteric and respiratory pathogens and diseases in unvaccinated pre-weaned dairy heifers, in their first 2 weeks of life (exam 1), and at 4- to 8-weeks old (exam 2). Heifers from 20 dairy herds were examined and sampled twice for respiratory and enteric pathogens and diseases. Respiratory health score and ultrasonographic lung consolidation were assessed, and nasopharyngeal swabs, blood samples, and feces samples were collected. The prevalence for each disease and pathogen was described, and the difference between exams 1 and 2 was assessed. A total of 198 heifers were included at exam 1, and 182 of them were examined again at exam 2. At exam 1, the prevalence of respiratory diseases (positive clinical score or presence of lung consolidation) and diarrhea was 18% and 23%, respectively. At exam 2, the prevalence of respiratory diseases and diarrhea was 62% and 13%, respectively. Heifers were less likely to have respiratory diseases and pathogens at exam 1 than exam 2, and were more likely to have diarrhea at exam 1 than exam 2. These results help in understanding the dynamic of respiratory and enteric pathogens and diseases.

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 score0.477
Threshold uncertainty score0.665

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 head0.013
GPT teacher head0.230
Teacher spread0.218 · 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

Citations4
Published2021
Admission routes3
Has abstractyes

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