Accuracy of international evaluations in predicting French estimated breeding values of foreign Holstein bulls
Bibliographic record
Abstract
For foreign bulls, one of the first information available for breeding decision in France comes from international evaluations based on foreign daughters only. Our purpose was to investigate whether or not this information was an accurate predictor of the future French estimated breeding values (EBVs) of foreign bulls for 11 traits: 5 production traits, somatic cell scores and 5 conformation traits. The correlation and the mean difference between Interbull (before including French daughters) and French EBVs were computed for foreign “AI imported” Holstein bulls. The observed correlations were high (above 87%), especially for the production traits and stature (above 94%). The lowest correlations were for fore udder attachment (87%) and somatic cell count (88%). The French EBVs were generally smaller than Interbull EBVs, but differences were quite small (less than 10% of genetic standard deviation). These differences were generally not statistically significant except for the mean difference for stature that reached -20% of genetic standard deviation. Further investigations showed that the country of origin of bulls (Canada, United States or European Union) did not influence correlations and mean differences. In conclusion, this study revealed that Interbull evaluations were accurate French EBVs predictors of foreign bulls, and confirmed that they can be used for breeding decisions without moderation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".