Genetic parameters for performance and carcass traits in a paternal 1 lineage of broiler
Bibliographic record
Abstract
The objective of this study was to estimate variance components for performance and carcass traits in a paternal broiler line. The (co)variance components were estimated by the restricted maximum likelihood method applied to the animal model, including the fixed effect of group (sex and hatch) and additive genetic and residual as random effects. Estimated heritability for performance traits ranged from 0.09 to 0.42. The genetic correlations between traits ranged from -0.50 to 0.97. The heritability estimates of feed intake, weight gain, and feed conversion from 35 to 41 days of age were of low magnitude. The genetic correlations among them were favorable to genetic selection. These results suggest that moderate genetic gain can be obtained to the feed intake and weight gain when the selection criterion is the body weight and prime cuts traits. The feed conversion that had low heritability estimation and low genetic correlation with the body weight and prime cut traits needs to pay greater attention due to the economic importance in the high-meat production lineage breeding programs.
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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 | 0.001 |
| 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 | 0.000 |
| 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".