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Record W4320717583 · doi:10.3168/jds.2022-22366

A randomized controlled trial investigating the effect of transport duration and age at transport on surplus dairy calves: Part I. Impact on health and growth

2023· article· en· W4320717583 on OpenAlexafffundabout
H.M. Goetz, K.C. Creutzinger, D.F. Kelton, J.H.C. Costa, Charlotte B. Winder, D.L. Renaud

Bibliographic record

VenueJournal of Dairy Science · 2023
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
FundersDairy Farmers of Canada
KeywordsMedicinePoisson regressionColostrumRandomized controlled trialBovine respiratory diseaseAnimal scienceAnimal husbandryDiarrheaEnvironmental healthVeterinary medicineBiologyInternal medicineAgricultureImmunology

Abstract

fetched live from OpenAlex

Calves arriving to veal and dairy-beef facilities in poor condition are at risk of future health challenges and reduced growth rates, and limited knowledge is available on how time in transit affects subsequent health and growth of these animals. The objective of this randomized controlled trial was to understand the effects of transport duration on diarrhea, respiratory disease, and growth of surplus calves destined for veal production following 6, 12, or 16 h of continuous road transport. Surplus dairy calves (n = 175; 7 transport cohorts) from 5 commercial dairy farms in Ontario, Canada, were enrolled on the day of birth. These calves were clinically examined daily on the source farms until the day before transport and on a daily basis for the first 14 d at the veal farm. On the day of transport, they were randomly assigned to 6, 12, or 16 h of transport to a veal farm. A blood sample was collected between 24 and 48 h of birth to assess transfer of passive immunity status. Calves were weighed at birth, before and immediately after transport, as well as 24, 48, and 72 h after unloading. Calves were also weighed 14 and 50 d after transport. Health exams were conducted daily at the source farm, immediately before and after transport, and once daily for 14 d thereafter to evaluate clinical signs of diarrhea, respiratory disease, dehydration, and navel inflammation. Mixed effects Poisson regression models were used to evaluate variables associated with the number of days with abnormal respiratory and fecal scores, whereas mixed logistic regression models with repeated measures were built to assess the probability of a calf having abnormal respiratory scores, abnormal fecal scores, or dehydration by day after arrival to the facility. A mixed model with repeated measures was used to evaluate calf weight at each time point at which body weight was measured after transport, whereas a mixed linear regression model was used to evaluate factors associated with average daily gain (ADG) in the 50 d after transport. Calves transported for 16 h had greater incidence of abnormal fecal scores compared with 6 h in the 14 d after transport. In addition, an interaction between age and duration of transport on the number of days with abnormal respiratory scores was identified, where calves older than 7 d of age had reduced incidence of abnormal respiratory score compared with calves 2 to 6 d old, even when transported for 16 h. As for growth, age at transport was positively associated with ADG in the 50 d of observation; however, no differences were observed between transport duration groups. These findings highlight that transporting calves for a longer duration negatively affects subsequent health, and calves greater than 1 wk of age experience improved health and growth after transport compared with their younger counterparts.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.045
GPT teacher head0.356
Teacher spread0.310 · 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 designRandomized trial
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

Citations27
Published2023
Admission routes3
Has abstractyes

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