Evaluation of Castration Technique, Pain Management, and Castration Timing in Young Feedlot Bulls in Alberta
Bibliographic record
Abstract
A randomized commercial feedlot study was conducted to evaluate the effect of castration technique (band castration (BC) versus surgical castration (SC)), pain management (anesthesia/analgesia (AA) versus no anesthesia/analgesia (NA)), and castration timing (allocation (DO) versus 70 days post-allocation (D70)) on animal health, feedlot performance, and carcass characteristic variables of young bulls. There were 960 bulls and 48 pens used in a complete block design, with no commingling of animals from different experimental groups in the same pens. In the preliminary feedlot performance data summary from allocation to D159, ADG ( +0.051 lb./day, P=0.188) and DM:G (-0.117, P=0.060) were improved in pens castrated at DO versus pens castrated at D70; ADG ( +0.076 lb./day, P=0.049) and DM:G (-0.069, P=0.264) were improved in pens castrated using BQ versus pens castrated using SC; and ADG ( +0.025 lb/day, P=0.511) and DM:G (-0.079, P=0.204) were improved in pens castrated with NA versus those castrated with AA. There were no significant interactions detected between castration timing, castration technique, and pain management strategies. There were minimal differences in mortality from DO to D159 between the pens in each of the castration options (DO versus D70; BC versus SC; or AA versus NA). The preliminary data from DO to D159 are interesting; however, final data from allocation through slaughter are necessary to complete the overall assessment of each castration option. Understanding the relative cost-effectiveness of each castration option will help bridge the gap that currently exists in determining optimal castration management in commercial feedlot settings.
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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 | 0.001 | 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 | 0.001 |
| 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".