Consistency of Maturity Rate for Milk Yield Across Countries and Generations
Bibliographic record
Abstract
Differences among bulls in maturity rate of their daughters for milk yield were investigated. Milk records for US Holsteins with first-parity calving dates between 1960 and 1998 were used to calculate 3 evaluations for bulls based on daughter records from parity 1, parities 1 and 2, and parities 1, 2, and 3. The 3 evaluations were used to estimate parity-specific evaluations for parities 2 and 3. Maturity rate of Holstein bull daughters in Canada and The Netherlands was compared with that for daughters of the same bulls in the United States by using official November 2004 Canadian and August 2005 Dutch parity-specific evaluations. For bulls with > or = 500 first-parity daughters, correlations among parity-specific evaluations within country and birth year of bull were 0.88 between parities 1 and 2, 0.84 between parities 1 and 3, and 0.96 between parities 2 and 3 for the United States; 0.90, 0.86, and 0.97, respectively, for Canada; and 0.92, 0.89, and 0.98, respectively, for The Netherlands. Correlations between Canada and the United States for within-country differences between evaluations for parities 1 and 2 were 0.72 for bulls with > or = 50 first-parity daughters and 0.89 for bulls with > or = 500 first-parity daughters; corresponding correlations between The Netherlands and the United States were 0.66 and 0.82. Correlations between countries for differences between evaluations for parities 1 and 3 were slightly less, and corresponding correlations between evaluations for parities 2 and 3 were still lower. To establish whether differences between parity-specific evaluations were genetic, comparisons were made across a generation. Coefficients for regression of son on sire within country and birth years of sire and son for parity-specific evaluations and differences between parity-specific evaluations ranged from 0.35 to 0.53, with standard errors of < or = 0.04. Differences in maturity rate of bull daughters were quite consistent across country, and those differences were transmitted to the sons' daughters. Modeling to account for maturity differences should increase the accuracy of US evaluations and reduce fluctuation between evaluations, especially for bulls with daughters that deviate substantially from the population mean for maturity rate for milk yield.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".