Reducing the effect of parent averages from animal solutions in mixed model equations
Why this work is in the frame
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Bibliographic record
Abstract
Summary Selection of animals based on their BLUP evaluations from an animal model results in animals that are closely related which leads to increased rates of inbreeding. The tendency for higher inbreeding rates is greater at low heritability values. Several attempts have been made to reduce the impact of parent average breeding values from animals evaluations in order to reduce inbreeding while not sacrificing genetic response. A method that modifies the rules for forming the inverse of the additive genetic relationship matrix for use in best linear unbiased estimation of breeding values via an animal model was developed. This method and several others were compared analytically and empirically, from the perspective of partitioning the animal solutions into contributions from the data, from progeny, and from the parent average. The ratio of genetic progress to average level of inbreeding showed that the modified relationship matrix method was superior to the other methods. Similar results could be obtained by using artificially high heritability in a usual BLUP analysis.
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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 it