656. A genomic evaluation of genotype-by-environment interactions for foot scores in American and Australian Angus cattle
Bibliographic record
Abstract
The main goal of this study was to investigate the feasibility of an across-country genomic evaluation for claw-set and foot angle scores in North American and Australian Angus populations, by analysing within and across-country genotype-by-environment interactions (G×E). In total, 123,322 and 1.13M animals had phenotype and genotype information. Reaction norm models fitting environmental gradients based on the effects of management group and bivariate animal models were used to evaluate genetic correlation within-and across-countries, respectively. Similar heritability estimates were obtained for both North American and Australian populations (0.22-0.25), and moderate-to-high genetic correlations between foot scores (claw-set: 0.73; foot angle: 0.51) were observed between countries. On average, high genetic correlations (>0.90) were observed among pairs of environmental gradients within countries. However, moderate correlations were observed among contrasting environmental gradients (e.g. 0.50), indicating moderate G×E. In general, gains in both theoretical and prediction accuracy of genomic estimated breeding values from a joint- versus within-country genomic evaluation were observed.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".