Investigation of genotype by country interactions for growth traits for Charolais populations in Australia, Canada, New Zealand and USA
Why this work is in the frame
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Bibliographic record
Abstract
Evidence of heterogeneity of parameters and genotype by country interactions was investigated for birth weight (BWT),weaning weight (WWT) and postweaning gain (PWG) between Australian (AUS), Canadian (CAN), New Zealand (NZ) andUSA populations of Charolais cattle. An animal model was fit to data sets for each individual country to compare the within countryparameter estimates for homogeneity. The direct heritability estimates of BWT in AUS (0.34) and NZ (0.31) were lessthan CAN (0.55) and USA (0.47). Maternal BWT heritabilities (0.13–0.18), direct WWT heritabilities (0.22–0.27), andmaternal WWT heritabilities (0.12–0.18) were similar across all four countries. Direct PWG heritability for AUS (0.14) wassmaller than the same estimate in the other three countries (0.24–0.31). The phenotypic variances for all three traits were similaracross AUS, CAN and USA; however, NZ was higher for BWT and WWT and lower for PWG. A multiple trait animal modelthat considered each trait as a different trait in each country was also fit to the data for pairs of countries. Direct (maternal)estimated genetic correlations for BWT for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.88 (0.86),0.85 (0.82), 0.88 (0.82), 0.85 (0.83), and 0.84 (0.80), respectively. Direct (maternal) estimated genetic correlations for WWT forAUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.96 (0.91), 0.95 (0.90), 0.95 (0.91), 0.95 (0.92), and0.95 (0.92), respectively. Direct estimated genetic correlations for PWG for AUS–CAN, AUS–USA, USA–CAN, NZ–CANand NZ–USA were 0.89, 0.91, 0.94, 0.90, and 0.91, respectively. The magnitude of the across-country genetic correlationsindicates that genotype by country interactions were biologically unimportant. However, strong evidence exists forheterogeneity of parameters across the countries for some traits and effects. Therefore, combining these countries into one singleanalysis to produce a common set of genetic values will depend on the development of methods to adjust for heterogeneousparameters for models containing both direct and maternal effects, and for circumstances where constant variance ratios orheritabilities are not present across populations.
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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