Assessing the performance response of laying hens to intake levels of digestible balanced protein from 27 to 66 wk of age
Bibliographic record
Abstract
Laying hens continue to improve in egg production (EP) and feed efficiency (FE), and therefore, it is relevant to re-examine their digestible balanced protein (BP) requirements. From 27 to 66 wk of age, hens (Lohmann-LSL Lite) were fed diets designed to provide 550, 625, 700, 775, or 850 mg hen−1 d−1 of amino acid balanced digestible lysine (Dlys). Response criteria included EP, egg weight (EW), feed intake (FI), mortality, egg mass (EM), egg size classifications, FE (kg feed kg−1 EM), and lysine efficiency (LE; mg Dlys g−1 EM). The experiment was a completely randomized design, and data were analyzed using regression analysis. Differences were considered significant if P ≤ 0.05. Hen-day (HD) EP, EW, EM, FI, and LE increased and FE and mortality decreased in a quadratic fashion with increasing Dlys intake, while the proportion of cracked eggs increased linearly. Egg size classifications increased linearly (jumbo, extra-large) and quadratically (large) or decreased in a quadratic manner (medium, small) with increasing Dlys intake. Maximum HDEP, EW, and EM, and minimum FE were achieved at 769, 903, 836, and 839 mg hen−1 d−1 intake of Dlys, respectively. In conclusion, the digestible BP requirement of laying hens varies with response criteria.
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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 | 0.001 |
| 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".