Bibliographic record
Abstract
This manuscript reports on the main problems decreasing productivity of dairy cows (e.g. fatty liver syndrome and poor fertility) and how antioxidants could enhance it. High producing dairy cows are prone to oxidative stress, and the situation can be exacerbated under certain environmental, physiological, and dietary conditions. Antioxidants have important effects on the expression of genes involved in the antioxidant status, which may enhance animal health and reproduction. Moreover, antioxidants may contribute to decrease the incidence of spontaneous oxidized flavour in milk enriched in polyunsaturated fatty acids. Plant lignans are strong antioxidants and flax is the richest source of plant lignans. Flax lignans are converted in the mammalian lignans enterolactone and enterodiol. The main mammalian lignan in milk is enterolactone and flax lignans are converted in enterolactone mainly under the action of ruminal microbiota. Therefore, ruminal microbiota may be the most important flora to target for plant lignan metabolism in order to increase concentration of mammalian lignan antioxidants in milk of dairy cows. However, more research is required to improve our knowledge on metabolism of other antioxidants in dairy cows and how they can contribute in decreasing milk oxidation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".