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Record W2740258637 · doi:10.3168/jds.2016-12157

Short communication: Prevalence of digital dermatitis in Canadian dairy cattle classified as high, average, or low antibody- and cell-mediated immune responders

2017· article· en· W2740258637 on OpenAlexafffundabout
S. Cartwright, F. Malchiodi, K.A. Thompson-Crispi, F. Miglior, Bonnie A. Mallard

Bibliographic record

VenueJournal of Dairy Science · 2017
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsNutreco (Canada)University of Guelph
FundersAgriculture and Agri-Food CanadaCanadian Dairy CommissionDairy Farmers of Canada
KeywordsLamenessDairy cattleHerdHoofMastitisMedicineLactationVeterinary medicineAnimal scienceBiologyPregnancySurgery

Abstract

fetched live from OpenAlex

Lameness is a major animal welfare issue affecting Canadian dairy producers, and it can lead to production, reproduction, and health problems in dairy cattle herds. Although several different lesions affect dairy cattle hooves, studies show that digital dermatitis is the most common lesion identified in Canadian dairy herds. It has also been shown that dairy cattle classified as having high immune response (IR) have lower incidence of disease compared with those animals with average and low IR; therefore, it has been hypothesized that IR plays a role in preventing infectious hoof lesions. The objective of this study was to compare the prevalence of digital dermatitis in Canadian dairy cattle that were classified for antibody-mediated (AMIR) and cell-mediated (CMIR) immune response. Cattle (n = 329) from 5 commercial dairy farms in Ontario were evaluated for IR using a patented test protocol that captures both AMIR and CMIR. Individuals were classified as high, average, or low responders based on standardized residuals for AMIR and CMIR. Residuals were calculated using a general linear model that included the effects of herd, parity, stage of lactation, and stage of pregnancy. Hoof health data were collected from 2011 to 2013 by the farm's hoof trimmer using Hoof Supervisor software (KS Dairy Consulting Inc., Dresser, WI). All trim events were included for each animal, and lesions were assessed as a binary trait at each trim event. Hoof health data were analyzed using a mixed model that included the effects of herd, stage of lactation (at trim date), parity (at trim date), IR category (high, average, and low), and the random effect of animal. All data were presented as prevalence within IR category. Results showed that cows with high AMIR had significantly lower prevalence of digital dermatitis than cattle with average and low AMIR. No significant difference in prevalence of digital dermatitis was observed between high, average, and low CMIR cows. These results indicate that having more robust AMIR is associated with lower prevalence of digital dermatitis hoof lesions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.037
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.043
GPT teacher head0.339
Teacher spread0.296 · 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

Citations23
Published2017
Admission routes3
Has abstractyes

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