Characterization of Dairy Production Systems in Countries that Participate in the International Bull Evaluation Service
Bibliographic record
Abstract
The International Bull Evaluation Service Centre has routinely calculated international dairy sire evaluations since 1994. Production systems vary between countries and between herds within a country, and these differences can cause significant genotype x environment interactions. First-lactation records of Holstein cows calving from January 1, 1990 through December 31, 1997, were used in this study. Countries that provided data for this study included Australia, Austria, Belgium, Canada, Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the United States. Country means were calculated for 13 variables related to climate, herd management, and genetic background. These variables were considered as possible causes of genotype by environment interaction. Highest peak yields were found in Israel and the United States at 31.4 and 30.5 kg, respectively. New Zealand and Estonia had the lowest daily peak yields at 17.1 and 18.9 kg, respectively. This was consistent with genetic differences between these countries, because Israel had the highest average predicted transmitting abilities (PTA) milk among sires, while Estonia had the lowest PTA milk. Persistency of lactation, defined as milk yield at 240 d postpartum divided by milk yield at 60 d postpartum, was highest in the Czech Republic and Estonia at 1.34, and lowest in Israel at 1.05. Herd size also varied substantially between countries, ranging from 2.3 first-lactation cows per herd-year in Finland to 62 per herd-year in Hungary. In summary, tremendous variation exists between the leading dairy countries in management, genetic, and climatic factors.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".