Lactation Persistency as a Component Trait of the Selection Index and Increase in Reliability by Using Single Nucleotide Polymorphism in Net Merit Defined as the First Five Lactation Milk Yields and Herd Life
Bibliographic record
Abstract
We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation (rG) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL (rG = 0.118 and 0.257, respectively).
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".