Genetic correlations between female fertility and postweaning growth and feed efficiency traits in multibreed beef cattle
Bibliographic record
Abstract
With selection in beef cattle now incorporating feed efficiency, knowing the relationship with other traits is needed. Genetic relationships were estimated with an animal model in ASReml with a three-generation pedigree inclusive of 2882 animals. Multibreed data from two Ontario beef research farms with fertility traits were available on 1366 females and postweaning traits, including feed efficiency on 1297 individuals. Estimates of heritability for fertility traits were low to moderate ranging from 0.03 ± 0.01 for pregnancy rate to 0.21 ± 0.02 for gestation length, and postweaning traits were moderate to high with feed conversion ratio at 0.22 ± 0.06 to mid-metabolic weight at 0.89 ± 0.01. Both dry matter intake and mid-metabolic weight were genetically correlated with most fertility traits from −0.52 to 0.34. The genetic correlation between average daily gain and days to calving was moderately negative (–0.33 ± 0.16) as was residual feed intake with days to calving (–0.34 ± 0.17). Bigger cows with more feed intake and faster growth were more fertile, and residual feed intake had an unfavorable genetic correlation with days to calving, indicating that programs to select for feed efficiency should include fertility simultaneously in a selection index.
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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".