MétaCan
Menu
Back to cohort
Record W2032052380 · doi:10.3168/jds.2013-6921

Reduced stocking density mitigates the negative effects of regrouping in dairy cattle

2014· article· en· W2032052380 on OpenAlexafffund
Ali Talebi, M.A.G. von Keyserlingk, E. Telezhenko, Daniel M. Weary

Bibliographic record

VenueJournal of Dairy Science · 2014
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaZoetisDairy Farmers of Canada
KeywordsStockingAnimal scienceDairy cattleBiology

Abstract

fetched live from OpenAlex

In freestall systems, cows are frequently moved among pens and regrouped. This practice involves mixing unfamiliar cows, and can result in changes in stocking density after regrouping. Both regrouping and changes in stocking density can affect cow welfare, but no study to date has assessed the combined effects. The aim of this study was to test if reductions in stocking density can mitigate the responses to regrouping. By manipulating group size (6 vs. 12 cows) and pen size (12 vs. 24 stalls), 3 different stocking densities were created (25, 50, and 100%). Four groups of Holstein cows were regrouped weekly for 4 wk and the stocking density changed at regrouping. The change in density varied as follows: a decrease by a factor of 4 (100 to 25%), a decrease by a factor of 2 (100 to 50% or 50 to 25%), no change (50 to 50%), an increase by a factor of 2 (25 to 50% or 50 to 100%), and an increase by a factor of 4 (25 to 100%). Displacements at the feeding area, feeding time, and lying time were scored. The daily means for each group were used to calculate the differences in responses from 1d before to 1d after each regrouping. The number of displacements at the feed bunk decreased and lying time increased when stocking density decreased at regrouping. In conclusion, increases in competitive behavior and the associated decrease in lying times can be mitigated by reducing stocking density when regrouping dairy cows.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.263

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 studies0.0000.001
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 head0.033
GPT teacher head0.319
Teacher spread0.287 · 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

Citations46
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Dairy ScienceSame topicAnimal Behavior and Welfare StudiesFrench-language works237,207