Progeny Testing and Selection Intensity for Holstein Bulls in Different Countries
Bibliographic record
Abstract
International Bull Evaluation Service (Interbull) Holstein evaluations from February 1995 through February 2003 were used to determine characteristics of progeny testing for Holstein bulls in Australia, Canada, Denmark, France, Germany, Italy, New Zealand, Sweden, The Netherlands, and the United States. The decision to graduate a bull from progeny test (PT) was assumed to have been made based on the second Interbull evaluation, and graduation was defined as the addition of 200 daughters in the period 2.5 to 4.5 yr later. Mean bull age at PT decision varied across countries by 12 mo. Mean numbers of herds and daughters ranged from 39 to 111 and 54 to 144, respectively. Countries with higher requirements for official evaluations generally had more herds and daughters but older bulls at PT decision. Mean estimated breeding values for yield traits of sires of tested bulls were most similar across countries for fat, differing by only 6.4 kg. The four countries highest for sire protein differed only by 1 kg; however, the range was 12 kg. Percentages of bulls graduated ranged from 4.4 to 14.7 across countries. Selection intensities (standardized selection differentials) tended to be about 1.0 for yield traits. Selection intensities for somatic cell score were generally unfavorable, reflecting selection for negatively correlated yield traits. Reflecting variation in national breeding goals, selection intensities for stature were positive for most countries and highly negative for New Zealand. Selection intensity for fore udder was generally the lowest among the traits examined. All but one country showed positive selection for udder support. These statistics permit comparison of the components of PT programs across country, illustrating possible opportunities for improvement.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".