Effects of preslaughter electrolyte supplementation on the hydration and meat quality of cull dairy cows
Bibliographic record
Abstract
Two studies were conducted to evaluate the effect of preslaughter electrolyte supplementation on weight loss, hydration, and beef quality of cull dairy cows. Cows were withheld from feed before slaughter for 36 or 24 h, and ambient temperature ranged from 22 to 32°C or from 12 to 17°C for Exp. 1 and 2, respectively. In Exp. 1, cull dairy cows (n = 60) were given the control treatment (CON; n=30) or the on-farm electrolyte supplementation treatment (PRE; n=30). Cows on the PRE treatment tended to have a greater (P = 0.06) decrease in packed cell volume than did CON cows throughout the preslaughter period. Longissimus samples from PRE cows exhibited greater drip loss (P = 0.04) and tended (P = 0.06) to have a lower 24-h pH than did samples from CON cows. In Exp. 2, cull dairy cows (n = 46) were given the CON (n = 16), PRE (n = 16), or posttransportation electrolyte supplementation treatment (n = 14). Cows on the PRE treatment tended to have a lower (P = 0.06) percentage of weight loss during transport than did untreated cows. Results from both experiments demonstrated the potential for preslaughter electrolyte supplementation to attenuate the negative effects of stressors on cull dairy cows, but supplementation appears to be more effective during periods of hot weather and extended feed withdrawal.
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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 | 0.001 |
| 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 | 0.001 | 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".