Differences between reproductive traits in beef bulls used for multiple-sire breeding under range conditions
Bibliographic record
Abstract
Brauner, C. C., Menezes, L. M., Lemes, J. S. and Pimentel, M. A. 2014. Differences between reproductive traits in beef bulls used for multiple-sire breeding under range conditions. Can. J. Anim. Sci. 94: 647–652. The aim of this study was to evaluate the reproductive traits (scrotal circumference and semen quality) of different breeds of beef bulls used for multiple-sire breeding under range conditions, as well as to verify the relation between four sperm concentration scores and the reproductive traits of beef bulls. Two hundred and one bulls of three different breeds (Angus, Nelore and Brangus) and three different age groups (18, 24 and 36 mo old) were evaluated. Angus showed better (P>0.05) reproductive traits than Brangus and Nelore bulls, in which scrotal circumference, mass motility spermatozoa, motility spermatozoa, as well as spermatic vigor were greater than those of other breeds. Two-year-old bulls demonstrated better reproductive traits as compared with the other age groups. The sperm concentration score had a linear effect (P<0.01) on all reproductive traits evaluated, and the same evidence was also detected for body weight. It was concluded that genetic groups should be considered differently for multiple-sire breeding under range conditions, especially because Bos taurus and Bos indicus have significant reproductive trait differences. Moreover, the sperm concentration score can be used as an auxiliary method of semen quality in beef bulls, having a positive relation with other breeding soundness evaluation traits.
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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) | 0.001 | 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".