Production and metabolic consequences of high-energy and low-crude-protein diet fed to 49-wk-old Shaver white leghorn without or with top-dressed organic selenium
Bibliographic record
Abstract
Production and metabolic consequences of feeding 49-wk-old Shaver white hens a high-energy low-crude-protein (HELP) diet were investigated over 6 wk. The test diets included standard diet [2750 kcal kg−1 apparent metabolizable energy (AME) and 17.5% crude protein (CP)], HELP (3000 kcal kg−1 of AME and 13.0% CP) diet, and HELP top dressed with selenium (HELP + Se). All diets had 0.3 mg Se kg−1 as part of premix. Hens (33) were procured, three birds necropsied for baseline liver samples, and the rest placed in individual cages and allocated diets (n = 10). Feed intake (FI), hen day egg production (HDEP), and egg weight (EW) were monitored weekly. Plasma and liver samples were collected from all birds. Birds fed standard and HELP diets had similar (P > 0.05) FI (with exception of weeks 4 and 5) and HDEP, whereas HELP + Se depressed (P < 0.05) feed and nutrient intake at weeks 5 and 6, HDEP, and EW. There were no (P > 0.05) diet effects on hepatic weight and crude fat content. Birds fed HELP diets had lower (P > 0.05) concentration of plasma total protein, macrominerals, and some enzymes. Overall, HELP diet had minimal impact on production and metabolism; however, addition of Se had negative effects on hen performance.
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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".