An investigation of hair cortisol as a measure of long-term stress in beef cattle: results from a castration study
Bibliographic record
Abstract
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.
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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 | 0.001 |
| 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".