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Record W4414518160 · doi:10.3390/ani15192788

Impacts of Maternal Bovine Appeasing Substance Administered at Weaning on Behavioral and Physiological Adaptation of Beef Heifers to the Feedlot

2025· article· en· W4414518160 on OpenAlexaff
Désirée Gellatly, Yaogeng Lei, Alison Neale, Emilie Edgar, Brittany Bloomfield, Brianna Elliot, I. I. Wenger, Sean Thompson

Bibliographic record

VenueAnimals · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsOlds College
Fundersnot available
KeywordsFeedlotRuminationHematocritWeaningRectal temperature

Abstract

fetched live from OpenAlex

The effects of administering 10 mL of maternal bovine appeasing substance (mBAS) or water (control; CT) at weaning (day 0) before transport on feedlot adaptation and efficiency were evaluated in twenty-two Angus-influenced heifers (n = 11/treatment) over 28 days. Body weight (BW), salivary cortisol, blood for complete blood cell count, rectal temperature, chute score and exit speed were collected on days 0, 14 and 27. Intake, feeding duration, frequency and rate, as well as activity and rumination were monitored daily using automated systems. Average daily gain (ADG) and gain-to-feed ratio (G:F) were calculated for each 14-day interval as well as for the entire feeding period. Treated heifers spent less time eating (p ≤ 0.06) on weeks 1 and 2, with greater feeding rate and activity (p < 0.01) in week 1, followed by reduced activity (p ≤ 0.05) in weeks 2, 3 and 4. Rumination was longer (p < 0.05) in weeks 3 and 4, coinciding with greater (p ≤ 0.05) final BW, ADG0–27, ADG14–27, and G:F0–27, G:F14–27. Lymphocyte and hematocrit were lower (p < 0.05) on days 14 and 27, respectively, and platelets tended to be greater (p = 0.08) than CT for the entire period. Treated heifers achieved numerically greater profit margins than CT. Overall, mBAS enhanced feedlot adaptability post-weaning, improving production efficiency, which may translate into potential profitability; however, this interpretation should be viewed cautiously considering some design limitations.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.870
Threshold uncertainty score0.132

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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