Genetic correlations among selected traits in Canadian Holsteins
Bibliographic record
Abstract
In the Canadian dairy industry, there are currently over 80 traits routinely evaluated, and more areconsidered for potential selection. Particularly, in the last few years, recording has commenced for several newphenotypes required to introduce novel traits with high economic importance into the selection program.However, without a systematic estimation of the genetic correlations that exist among traits, the potential resultsof indirect selection are unknown. Therefore, 29 traits representative of the trait diversity for first lactationCanadian animals were selected. Their two-by-two genetic correlations were estimated from a dataset of 62 498first lactation Holstein cows, using a Markov Chain Monte Carlo Gibbs sampling approach. The general tendenciesamong the groups of traits confirm that production traits are negatively correlated with fertility traits and thatfunctional traits are positively correlated with one another. The association of udder depth with fertility anddisease resistance has also been highlighted. This contribution offers a comprehensive overview of current esti-mates across traits and includes correlations with novel traits that constitute an original addition to the literature.These new estimates can be used for newly developed genomic evaluation models and possibly lead to more accu-rate estimations of the dairy cows’overall genetic merit.
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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 | 0.001 |
| 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".