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Record W3114560055 · doi:10.3168/jds.2019-17665

Making tiestalls more comfortable: I. Adjusting tie-rail height and forward position to improve dairy cows' ability to rise and lie down

2020· article· en· W3114560055 on OpenAlexafffundabout
J. St John, J. Rushen, Steve Adam, E. Vasseur

Bibliographic record

VenueJournal of Dairy Science · 2020
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNovalaitDairy Farmers of CanadaNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsAnimal scienceStall (fluid mechanics)LyingSignificant differenceMathematicsMedicineEngineeringBiologyStatistics

Abstract

fetched live from OpenAlex

The overall goal of the study was to develop new recommendations for tie-rail placement combining both vertical and horizontal positions to improve dairy cow welfare. Four treatments were tested: 2 new tie-rail positions that followed the natural neckline of cows when feeding and rising [neckline 1 (NL1), neckline 2 (NL2)], current recommendation (CR), and the average tie-rail position currently found on Quebec farms (current average on farm; CF). All other stall dimensions followed CR based on average cow size. Forty-eight cows blocked by parity and stage of lactation were randomly allocated to a treatment for 10 wk. Live scoring was performed weekly to evaluate injury, cow and stall cleanliness, and bedding quantity. Daily lying time, lying bout frequency, and lying bout duration were continuously recorded using leg-mounted accelerometers. Cows were recorded 1 d/wk by overhead cameras to evaluate lying down and rising events. Tie-rail placement did not affect cow and stall cleanliness, bedding quantity, and lying time. All tie-rail placements tested resulted in neck injuries with the position of neck injuries shifting based on the change in tie-rail placement: CR increased in proximal neck injuries (mean ± standard deviation, difference in injury score from baseline: +0.89 ± 0.153) compared with NL2 (+0.06 ± 0.153), but decreased in medial neck injuries (-0.11 ± 0.166) compared with NL2 (+0.78 ± 0.166) and NL1 (+0.53 ± 0.166). All treatments showed a decrease over time in average lying intention time (mean, difference between overall short- and long-term: -5.8 s/event), lying-down time (-1.1 s/event), contact with stall during lying (-32.5%), slipping during lying (-9.1%), backward movement on knees during rising (-10.9%), contact with tie-rail during rising (-14.3%), and overall abnormal rising (-15.6%) over time. Although lying and rising ability improved over time, abnormal lying and rising behaviors were still highly prevalent in the long term. Overall, our results show that dairy cows are limited in their ability to move within their environment without coming in contact with the stall confines (tie-rail and divider bars), warranting further research to determine alternatives to metal tie-rail bars, such as a flexible bar or chain, or provide fewer obstacles through the elimination of some stall hardware.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.053
GPT teacher head0.340
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 source (direct Gemma or distilled Codex), 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

Citations14
Published2020
Admission routes3
Has abstractyes

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