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Record W2025616904 · doi:10.3168/jds.2014-8065

Competition during the milk-feeding stage influences the development of feeding behavior of pair-housed dairy calves

2014· article· en· W2025616904 on OpenAlexafffund
E.K. Miller-Cushon, Renée Bergeron, K.E. Leslie, G.J. Mason, T.J. DeVries

Bibliographic record

VenueJournal of Dairy Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsKellogg's (Canada)University of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural AffairsUniversity of Guelph
KeywordsMealAnimal scienceFeeding behaviorBiologyFood science

Abstract

fetched live from OpenAlex

This study investigated how the feeding behavior of pair-housed calves develops in response to reduced teat and feed place availability. Twenty Holstein bull calves were pair housed and provided with milk replacer (MR) and grain concentrate ad libitum via either (1) 1 teat and feed bucket/pen, such that calves could not feed simultaneously [competitive feeding (CF)] or (2) 2 teats and feed buckets/pen [noncompetitive feeding (NCF)]. The calves were weaned during wk 7 of life by incrementally diluting the MR. Postweaning, all pens were managed identically and offered a complete pelleted diet ad libitum via 2 feed buckets/pen (NCF) in period 1 (wk 8 and 9) and period 3 (wk 12 and 13) and exposed to a competitive challenge with CF in period 2 (wk 10 and 11). Feeding times and competitive interactions were recorded from video for 3 d/wk in wk 2, 4, and 6 and 2 d/wk in wk 8 to 13. Meal criteria were used to calculate daily meal frequency, meal time, and synchronized meal time (the percentage of meal time when calves within the pen were engaged in simultaneous meals). Milk replacer intake was subject to a treatment × week interaction, with calves in CF pens having lower MR intake (wk 2: 8.3 vs. 10.0 L/calf per day for CF vs. NCF), but compensating by increasing intake to a greater extent over time (wk 4-5: 13.3 vs. 11.7 L/d for CF vs. NCF). Corresponding to MR intake, meal frequencies and feeding times evolved differently over this period, increasing in CF pens and decreasing in NCF pens (wk 2: 5.8 vs. 11.1 and wk 4-6: 6.2 vs. 5.1 meals/d for CF vs. NCF). Calves in CF pens also spent less time engaged in synchronized meals (28 vs. 51% of meal time; standard error=7.1) and displaced each other 5 times more frequently during synchronized eating. Postweaning, calves in previously CF pens maintained 5 times greater displacement frequencies and had fewer overlapping meals than calves in previously NCF pens (34.5 vs. 40.7% of meals, respectively). Postweaning, when calves were all fed noncompetitively (2 buckets/pen in periods 1 and 3), calves previously fed CF had greater intakes in period 3 (4.87 vs. 4.44 kg/d) and a tendency for greater intake in period 1 (2.80 vs. 2.63 kg/d), greater rates of intake in period 3 (87.8 vs. 72.0 g/min) and a tendency for greater rates of intake in period 1 (44.3 vs. 38.9 g/min), and greater meal frequencies in both periods (11.1 vs. 9.9 meals/d). In the competitive challenge period (1 bucket/pen in period 2), intake, rates of intake, and meal frequencies were subject to treatment × week interactions: calves in NCF pens had lower intake and meal frequencies, but increased meal frequency, intake, and rate of intake over time to a greater extent than calves previously in CF pens. These results indicate that calves are able to adapt to moderate competition by increasing meal frequency and that behavioral responses to competition persist postweaning.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.258
Teacher spread0.227 · 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

Citations26
Published2014
Admission routes2
Has abstractyes

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