Short Communication: The Pre-transport management of antemortem stress in cattle: Impact on carcass yield
Bibliographic record
Abstract
Grumpelt, B., Hoffer, W., Curie, O., Jones, O., Jones, K., Kimmel, D., McDonald, B., Paterson, R. and Schaefer, A. 2015. Short Communication:The Pre-transport management of antemortem stress in cattle: Impact on carcass yield. Can. J. Anim. Sci. 95: 557–560. Transport and handling of cattle can have a significant impact on carcass weight loss. The purpose of the present study was to examine the effect of providing pre-transport nutritional therapy containing selective amino acids, electrolytes and an energy source, on carcass weight loss. One hundred and ninety British crossbred steers averaging 611 kg were used in the study. The treatment cattle received 1 kg of a nutritional supplement top dressed onto their normal silage diet 24 h prior to transport. Following a 1-h transport period the cattle were processed at a federally inspected beef plant and both hot and cold carcass yield as well as yield grade and quality grade were assessed. Cattle provided with pre-transport nutritional therapy demonstrated a reduction in percentage live weight loss (P<0.01) as well as 1.2% greater hot carcass yield as a proportion of pre-treatment farm weight (P<0.01). The data suggest the use of nutritional support pre-transport is beneficial to carcass yield.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".