Effect of dietary chelated copper and methionine and cysteine on performance, egg quality, and nutrient balance in brown laying hens from 20 to 49 wk old
Bibliographic record
Abstract
Using 960 brown laying hens from 20 to 48 wk of age, in a 4 × 5 factorial arrangement, the effects on production, quality of eggs, and nutrient balance of analysed 18, 41, 61, and 111 mg kg−1 of copper (Cu) and of 0.550%, 0.679%, 0.793%, 0.845%, and 0.948% of methionine and cysteine (Met + Cys) were evaluated. Treatments were administered to six replicate cages (eight hens per cage). At the 49th wk of age, 320 of these hens were kept under the same experimental conditions to evaluate the nutrient balance, and each treatment was allocated to four replicate cages (four hens per cage). The trend of interaction effect between Cu and Met + Cys levels was observed on egg weight and mass. The interaction between mineral and amino acid was characterized on egg quality variables. Quadratic equations indicated that increasing the dietary level of Cu reduced the estimate requirement of Met + Cys for hens. Across the entire experimental period, the total estimated Met + Cys level was 0.755% ± 0.021% based on the performance variables. As Cu increased in the diet, it decreased the estimated Met + Cys level to ensure egg weight, mass, and egg quality. Level of chelated Cu above 23 mg kg−1 may negatively affect the egg quality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".