Selection strategies for limiting the increase in ascites while increasing growth in broilers
Bibliographic record
Abstract
The objective of the current study was to compare the changes in a fitness trait when selection is performed for 5, 10, and 20 generations on a production trait that influenced its expression. Responses to single-trait selection for growth based on phenotype or animal model predictions were compared by computer simulation. Two-trait index selection was performed when a trait, related to the fitness trait, was included in the index with the production trait. The phenotypic expression of the fitness trait among the sibs was also considered as a selection factor for single-trait and two-trait index selection. For a fixed increase in the expression of the fitness trait, mass selection produced a larger increase in the production trait than did use of standard animal model best linear unbiased prediction under single-trait selection. The reduction in the genotypic mean of the fitness trait was accompanied by an increase in its phenotypic expression. The use of sib information and an indicator trait reduced the level of expression reached by the fitness trait.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".