Bibliographic record
Abstract
Lutein is being considered as a nutrient for prevention of macular degeneration in the aging population. Two experiments were designed to study the transfer efficiency of lutein from the layers' diet into the egg. In experiment 1, laying hens were fed corn-soy diets supplemented with 0, 125, 250, 375, 500, 625, 750, or 1000 ppm of lutein. After 30 d, eggs were collected and assayed for lutein. In a second study, layers were fed corn-soy diets or diets containing corn gluten meal and alfalfa, with or without added flaxseed. Diets in experiment 2 were supplemented with 0, 125, 250, or 500 ppm of lutein. Adding lutein to the layers' diet resulted in a significant (P < 0.01) increase in Roche color score of yolk within 7 d of supplementation. In experiment 1, lutein was transferred into the yolk (P < 0.01) increasing from a basal level of 0.3 mg to 1.5 mg/60 g of egg. However, there was no significant (P > 0.05) increase in yolk lutein with diet supplements >375 ppm. In the second experiment, using corn gluten meal and alfalfa further increased lutein content that leveled off at 2.2 mg/60 g of egg with a diet supplement of 500 ppm of lutein. Adding flax to these diets seemed to depress yolk lutein content. Yolk lutein content can be increased, although further studies are needed to investigate the major decline in transfer efficiency seen with higher levels of dietary supplementation.
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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) | 0.001 | 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".