Body weight optimization of broiler breeder hens. 1. Pullet growth, feed efficiency, carcass composition, and sexual maturation
Bibliographic record
Abstract
; prepubertal phase). Two-hundred-eighty-eight Ross 308 pullets were randomly assigned to the twelve BW growth trajectories and fed using a precision feeding system from 0 to 28 wk of age. Body composition variables were submitted to three-way ANOVA, with EG, I2, and age as fixed sources of variation. Analysis of covariance was conducted on the remaining dependent variables with EG as fixed effect, I2 as a continuous fixed effect, and age as continuous random effect. Differences were reported at P ≤ 0.05. The BW of females followed their target BW, and ADFI differed depending on the amount of feed required to achieve their respective BW targets. Breast fleshing score was 0.2 greater in the EG20 compared to EG0. The number of juvenile primary wing feathers and age at first egg decreased by 0.4 and 0.9 d, respectively, per wk of earlier I2. Advancing I2 resulted in birds with increased carcass fat deposition from 16 to 28 wk of age. Carcass fat was 1.3- to 1.6-fold greater in the EG20 only from 4 to 16 wk of age. Early growth increased mostly pullet muscle and skeletal characteristics whereas advancing I2 advanced sexual maturity and increased carcass fat deposition around sexual maturation time.
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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 | 0.000 |
| 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 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".