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Effect of castration timing, technique, and pain management on health and performance of young feedlot bulls in Alberta

2008· article· en· W137992129 on OpenAlexafffundabout
Calvin W. Booker, Sameeh M. Abutarbush, Oliver C Schunicht, Colleen M Pollock, Tye Perrett, Brian K Wildman, Sherry J. Hannon, Tom J Pittman, C. A. Jones, G. Kee Jim, Paul S. Morley

Bibliographic record

VenueThe Bovine Practitioner · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsAlberta Health Services
FundersBayer CanadaBayer HealthCare
KeywordsCastrationFeedlotAnimal scienceMedicineWeight gainVeterinary medicineBody weightBiologyInternal medicine

Abstract

fetched live from OpenAlex

A total of 956 feedlot bulls were randomly allocated to one of eight castration groups based on a combination of castration timing, castration technique and pain management options. Bulls castrated at allocation had a higher occurrence of undifferentiated fever (UF) (P=0.086) and a higher proportion of yield grade Canada 3 carcasses (P=0.002) than those castrated at 70 days post-allocation. Bulls castrated using a band had a lower occurrence of UF (P=0.021), improved average daily gain (live weight basis P=0.056 and carcass weight basis P=0.048), dry matter intake-to-gain ratio (live weight basis P=0.075 and carcass weight basis P=0.066), and higher proportions of quality-grade (QG) Canada Prime carcasses (P=0.018) and QG Canada A carcasses (P=0.020) than bulls castrated surgically. There were no significant (P≥0.100) differences in animal health or feedlot performance between bulls given analgesia and anesthesia and those that were not. This study suggests that band castration is superior to surgical castration, and delayed castration is beneficial in bull calves with high risk of developing UF.

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 score0.247
Threshold uncertainty score0.151

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 studies0.0000.000
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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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

Citations10
Published2008
Admission routes3
Has abstractyes

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