Heritability of beef tenderness at different aging times and across breed comparisons
Bibliographic record
Abstract
Zwambag, A., Kelly, M., Schenkel, F., Mandell, I., Wilton, J. and Miller, S. 2013. Heritability of beef tenderness at different aging times and across breed comparisons. Can. J. Anim. Sci. 93: 307–312. The heritability of shear force at 7, 14 and 21 d was estimated from a crossbred population of beef cattle. The population consisted of approximately 1400 crossbred cattle that were predominantly the offspring of Angus, Simmental, Gelbvieh and Piedmontese sires bred to predominantly Angus and Simmental females. Significant breed effects on tenderness were found within each aging time and no effect of heterosis was detected. The heritability of shear force declined from 0.194 to 0.048 as aging time increased from 7 to 21 d, highlighting the effectiveness of aging as a tool to improve tenderness. The repeatability of shear force was also found to be moderate (0.53). However, as energy prices increase it may be attractive to reduce aging times, thus breeding animals that are more tender at shorter aging times would be beneficial. The heritability of tenderness found at shorter aging times would indicate that improvement in this trait would be possible within a population where phenotypes are available.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".