Short communication: Genetic parameters of milking temperament and milking speed in Canadian Holsteins
Bibliographic record
Abstract
The objectives of this study were to estimate genetic parameters of milking temperament (MT) and milking speed (MS) in Canadian Holsteins and to examine associations of bull proofs of MT and MS with other economically important traits. First-lactation data consisted of 1,940,092 and 2,620,175 cows for MT and MS, respectively. Milking temperament and MS were recorded on a scale from 1 to 5 from very nervous to very calm and from very slow to very fast, respectively. The linear animal model included the fixed effects of herd-year-season of calving, stage of lactation, age at first calving, and the random effects of animal and residual. Both single-trait and bivariate analyses were carried out to estimate genetic parameters of MT and MS. For genetic parameter estimation, 20,000 records from randomly selected herds were used. However, for breeding value estimation, all records were included. Heritability values were 0.128 and 0.139 for MT and MS, respectively. The genetic correlation between MT and MS was 0.247. Analysis of bull proof correlation of MT and MS with other traits indicated that these traits were lowly correlated with a wide range of traits such as production, reproduction, conformation, and auxiliary 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".