Economic weights for genetic improvement of lactation persistency and milk yield
Bibliographic record
Abstract
This study aimed to establish a criterion for measuring the relative weight of lactation persistency (the ratio of yield at 280 d in milk to peak yield) in restricted selection index for the improvement of net merit comprising 3-parity total yield and total lactation persistency. The restricted selection index was compared with selection based on first-lactation total milk yield (I(1)), the first-two-lactation total yield (I(2)), and first-three-lactation total yield (I(3)). Results show that genetic response in net merit due to selection on restricted selection index could be greater than, equal to, or less than that due to the unrestricted index depending upon the relative weight of lactation persistency and the restriction level imposed. When the relative weight of total lactation persistency is equal to the criterion, the restricted selection index is equal to the selection method compared (I(1), I(2), or I(3)). The restricted selection index yielded a greater response when the relative weight of total lactation persistency was above the criterion, but a lower response when it was below the criterion. The criterion varied depending upon the restriction level (c) imposed and the selection criteria compared. A curvilinear relationship (concave curve) exists between the criterion and the restricted level. The criterion increases as the restriction level deviates in either direction from 1.5. Without prior information of the economic weight of lactation persistency, the imposition of the restriction level of 1.5 on lactation persistency would maximize change in net merit. The procedure presented allows for simultaneous modification of multi-parity lactation curves.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".