Partially substituting alfalfa hay with hemp forage promotes the health and well‐being of goats via altering ruminal and plasma metabolites and metabolic pathways
Bibliographic record
Abstract
Abstract Hemp forage (HF) seems a suitable forage for ruminants for its high nutritional value and rich phytochemicals that exert health and growth‐promoting activities. We investigated the effects of hemp‐related phytochemicals on rumen and plasma metabolism using metabolome when partially substituting alfalfa hay with HF in goat diets. Numbers of differential metabolites linearly increased with increasing HF substituting rate, approximately 50% of which were phytochemicals. Metabolic pathway enrichment analysis showed that the inclusion of HF greatly promoted steroid hormone biosynthesis, one carbon pool by folate, and retinol metabolism pathways in both rumen and plasma, which are beneficial for promoting animal health and well‐being and enhancing the quality of animal products. Some phytochemicals showed inhibitory activities on the growth of certain ruminal bacteria; meanwhile, the detected intermediate metabolites indicated degradation of the phytochemicals by ruminal microbes. These phytochemicals work individually and synergistically to alter ruminal and plasma metabolic pathways, thus exerting benefits in promoting the health and well‐being of animals.
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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".