Dose–responses of zinc–methionine supplements on growth, blood metabolites and gastrointestinal development in sheep
Bibliographic record
Abstract
The effects of zinc-methionine (Zn-Met) supplementation on growth, blood metabolites and gastrointestinal development were investigated in two experiments with sheep. The objective of Experiment 1 was to determine the effects of Zn-Met supplementation on hormones and metabolites involved in growth and energy balance regulation, while Experiment 2 aimed to determine the effects of Zn-Met on feed intake, body weight, gastrointestinal development and liver glycogen concentration in lamb. The animals were assigned to groups with different concentrations of dietary Zn-Met (0, 0.4, 0.8 and 1.2 g/day) in both experiments. In Experiment 1, feeding different doses of Zn-Met increased plasma insulin-like growth factor 1 (IGF-1) concentration, but it linearly decreased plasma growth hormone (GH). No differences were observed in blood cortisol, insulin and glucose concentrations among the treatments. In Experiment 2, addition of Zn-Met to the diets did not lead to changes in the body weights of the lambs. Both average daily gain and dry matter intake (DMI) increased linearly with increasing concentrations of dietary Zn-Met. Lambs receiving Zn-Met showed higher liver glycogen concentrations than the control. While significant increases were observed in the villus height and crypt depth in the duodenum and jejunum as a result of Zn-Met supplementation, no change was detected in blood glucose concentrations (p > 0.05). Our findings suggest that dietary Zn-Met may improve growth, energy balance and gastrointestinal development in sheep.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".