Genetic correlations among indicator traits for carcass composition measured in yearling beef bulls and finished feedlot steers
Bibliographic record
Abstract
Genetic correlations were examined among 10 live growth and ultrasound traits measured in yearling beef bulls (n = 2172) and four carcass traits measured in crossbred finished feedlot steers (n = 1031). Heritabilities ranged from 0.13 (bull ultrasound longissimus muscle width) to 0.83 (yearling bull hip height). Genetic correlations indicated that selecting yearling bulls for increased growth rate and hip height would lead to higher carcass weight, increased longissimus muscle area and reduced levels of carcass marbling in steers. Bull ultrasound fat depth was positively associated with both carcass fat depth and marbling score. Most ultrasound longissimus muscle size measurements in bulls were positively associated with each other and with carcass longissimus muscle area in steers, but the magnitude of the genetic correlation with carcass measurements depended on the bull longissimus muscle size trait in question. This suggests that longissimus muscle shape in bulls may be related to carcass weight, fat and muscle traits in steers. Results confirm that while ultrasound is a valuable tool for the genetic improvement of carcass traits in beef cattle, genetic correlations between live bull ultrasound and steer carcass traits less then unity suggest that selection would benefit from multiple trait evaluations in situations where reliable carcass data are available. Key words: Ultrasound, beef carcass, heritability, genetic correlation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".