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Record W4379058489 · doi:10.3168/jds.2023-23229

Effects of transportation duration on lying behavior in young surplus dairy calves

2023· article· en· W4379058489 on OpenAlexafffundabout
A. Bajus, D.L. Renaud, H.M. Goetz, M.A. Steele, D.F. Kelton, Kathryn L. Proudfoot, K.C. Creutzinger

Bibliographic record

VenueJournal of Dairy Science · 2023
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Prince Edward IslandUniversity of Guelph
FundersDairy Farmers of Canada
KeywordsLyingDuration (music)Animal scienceDairy cattleDairy industryBusinessAgricultural scienceFood scienceChemistryEnvironmental scienceBiologyMedicinePhysics

Abstract

fetched live from OpenAlex

Surplus dairy calves are commonly transported long distances from dairy farms to calf-raising facilities and livestock auctions. Current calf transportation research mainly describes physiological changes resulting from transportation. However, few studies have described the effects of transportation on calf behavior. The main objective of this study was to determine the effects of different durations of transportation (6, 12, and 16 h) on lying time and bouts in surplus dairy calves. A secondary objective of this study was to investigate whether calf age affected lying behavior around transportation. Surplus dairy calves (n = 175) were transported in 7 cohorts from 5 commercial dairy farms in Ontario to a single veal facility. On the day of transportation (d 0), calves were randomly assigned to 1 of 3 treatment groups: (1) 6 h (n = 60), (2) 12 h (n = 58), or (3) 16 h (n = 57) of continuous transportation by road. Calf lying and standing behaviors were recorded using HOBO data loggers (Hobo Pendant G Acceleration Data Logger, Onset Computer Corporation). Daily lying time (h/d) and bouts (no./d) were assessed from -1 to 3 d relative to transportation. The total time spent lying during transportation was assessed as the percentage of time lying (min lying/total min on the trailer × 100) from the time each calf was loaded onto the trailer until the time each calf was unloaded at the veal facility (n = 167). On the day of transportation (d 0), calves transported for 12 and 16 h spent less time lying (6 h: 17.1 h/d; 12 h: 15.9 h/d; 16 h: 15.0 h/d) and had more lying bouts (6 h: 21.9 bouts/d; 12 h: 25.8 bouts/d; 16 h: 29.8 bouts/d) compared with those transported for 6 h. On the day after transportation (d 1), calves transported for 16 h spent more time lying down than calves transported for 6 h (19.9 h/d vs. 18.8 h/d, respectively). In addition, during transportation, calves transported for 12 h and 16 h spent 5.8% and 7.6% more time lying down, respectively, than calves transported for 6 h. On each day relative to transportation (d -1 to 3), younger calves (2 to 5 d of age) spent a greater amount of time lying down than older calves (6 to 19 d of age) and, overall, had a greater number of lying bouts. The results of this study suggest that longer durations of transportation influence the lying behavior of surplus dairy calves, resulting in more fatigue during and after the journey and, therefore, potentially have negative implications for calf welfare. Additionally, longer durations of transportation may have greater influence on younger calves than older calves.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

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

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 head0.044
GPT teacher head0.345
Teacher spread0.301 · 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

Citations6
Published2023
Admission routes3
Has abstractyes

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