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Record W2592777807 · doi:10.1139/cjas-2016-0206

An investigation of hair cortisol as a measure of long-term stress in beef cattle: results from a castration study

2017· article· en· W2592777807 on OpenAlexafffundvenue
J. M. Stookey, Travis Marfleet, John Campbell, David M. Janz, Fernando J. Marqués, Yolande M. Seddon

Bibliographic record

VenueCanadian Journal of Animal Science · 2017
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Saskatchewan
FundersMinistry of Agriculture - Saskatchewan
KeywordsCastrationMeloxicamAnimal scienceBeef cattleSalineMedicineInternal medicineBiologyHormone

Abstract

fetched live from OpenAlex

The objectives were to (1) investigate the effectiveness of hair cortisol concentration (HCC) as a measure of long-term stress in beef cattle and (2) determine whether meloxicam would decrease postcastration stress. Bull calves on two farms [site 1: Hereford cross (n = 73); site 2: Black Angus (n = 85)] were assigned to three treatments: (1) surgical castration with saline (CS, n = 52), (2) surgical castration with meloxicam (CM, n = 54), and (3) sham castration with saline (S, n = 52), balanced for age. Hair was collected from the left hip on day 0, prior to castration, and day 14, after 2 wk of regrowth from the day 0 location. Standing time was recorded on 129 calves (CS = 47, CM = 42, S, = 40) from 0 to 7 d post castration. On day 14, CS calves had 13.8% greater HCC than S (P = 0.031) and tended to be higher than CM calves (P = 0.095); CM and S calves did not differ. Standing time did not differ between treatments. Lower HCC in CM compared with CS calves indicates that meloxicam may be effective at reducing postcastration stress. With differences between treatments, HCC shows promise as a technique for measuring long-term stress in beef cattle.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.093
GPT teacher head0.356
Teacher spread0.263 · 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

Citations20
Published2017
Admission routes3
Has abstractyes

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