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Record W2108371118 · doi:10.3168/jds.2011-4953

Effect of pen size, group size, and stocking density on activity in freestall-housed dairy cows

2012· article· en· W2108371118 on OpenAlexafffund
E. Telezhenko, M.A.G. von Keyserlingk, Ali Talebi, Daniel M. Weary

Bibliographic record

VenueJournal of Dairy Science · 2012
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaDairy Farmers of CanadaPfizer
KeywordsStockingAnimal scienceLatin squareMathematicsVideo recordingBiologyFood science

Abstract

fetched live from OpenAlex

The purpose was to determine the effects of the physical dimensions of the pen and group size and stocking density on cow activity. Cows (randomly assigned to 4 groups of 6 animals each) were tested in pens with 24 or 12 lying places and in groups with 12 or 6 cows. All groups were tested in each of the 4 treatments with treatment order allocated using a 4 × 4 Latin square. The distance moved and the number of movements were calculated using 5-min scan sampling of video recordings over a 48-h period. Time spent lying down, number of lying bouts, and the duration of each lying bout were recorded using activity sensors. Displacements at the feed bunk were assessed by continuous analysis of video for 3h after the delivery of the fresh feed in the afternoon. Cows moved greater distances when kept in a large versus small pens (330.2 vs. 270.1 ± 11.6 m/d; mean ± SE), irrespective of group size. Cows moved more often when kept in the larger pen (21.3 vs. 19.2 ± 0.63% of scans). The time spent lying down decreased when density increased (59.1 vs. 55.8 ± 2.3% of scans at 25% and 100% stocking, respectively). Treatment had no effect on the number of displacements at the feed bunk. Physical dimensions of the pen play an important role in how much cows move, and stocking density affects lying time.

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)0.003
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 score0.385
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.036
GPT teacher head0.335
Teacher spread0.299 · 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

Citations63
Published2012
Admission routes2
Has abstractyes

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