Dietary ginger ( <i>Zingiber officinale</i> ) enhances performance traits, biochemical and haematological indices of Turkey targeting mRNA gene expression
Bibliographic record
Abstract
Ginger rich in polyphenols, possesses various biomedical properties. Researchers investigated the effects of dietary ginger supplementation on turkey performance traits, biochemical parameters, haematological parameters and mRNA gene expression. Ginger root powder was administered at different doses (0, 10, 20 and 40 g/kg) to the turkeys. Notably, the 20 g/kg group exhibited improved performance traits and a higher broiler production efficiency factor (BPEF). Importantly, ginger was found to be safe for turkeys based on serum indices. Furthermore, the expression of several growth-related genes, including growth hormone receptor (GHR), insulin-like growth factor 1 (IGF-1), adenine nucleotide translocase (ANT), cyclooxygenase 3 (COX-3) and uncoupling protein 3 (UCP-3), was upregulated in the 20 g/kg enhancing their growth performance and economic efficiency in addition to keeping their health status safe. Therefore, Ginger root powder can be supplemented for turkey at a concentration of 2% as the addition of ginger powder is a long-term process.
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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".