Effect of a single dose of subcutaneous meloxicam before knife castration alone or combined with hot-iron branding on scrotal healing, inflammatory response, and behaviour in 2-mo-old beef calves over 42 d post procedure
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of a single subcutaneous injection of meloxicam on scrotal healing, inflammatory response, and behaviour in castrated or castrated and branded beef calves for 42 d post procedure. Seventy-two 2-mo-old Angus crossbred bull calves were used to assess the effects of procedure (Trt): (1) sham control, (2) knife castration, and (3) knife castration and hot-iron branding; and pain mitigation (Med): (1) nonmedicated and (2) medicated with meloxicam according to a 3 × 2 factorial design. Body weight, scrotal circumference (SC), and healing scores were collected weekly until day 42. Blood samples were collected weekly until day 42 to assess haptoglobin, serum amyloid-A, and complete blood cell count. Hair was collected on day −1 and day 42 to assess cortisol concentrations. Lying and standing behaviour were recorded for 42 d, whereas pain-related behaviours were recorded on days 7, 15, 22, 29, and 34 post procedure. The inflammatory response (SC) and duration of standing was greater (P < 0.05) in calves castrated and branded than those only castrated. However, meloxicam did not reduce inflammation or improve wound healing in either castrated or castrated and branded calves.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".