Effect of castration timing, technique, and pain management on health and performance of young feedlot bulls in Alberta
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".