Effects of dietary flaxseed and vitamin E on fermentation, nutrient disappearance, fatty acid biohydrogenation, and microbial protein synthesis using a simulated rumen (Rusitec)
Bibliographic record
Abstract
Two simulated rumens (Rusitecs) were used to assess the effects of flaxseed (FS) and (or) vitamin E (VE) on rumen fermentation, fatty acid (FA) biohydrogenation, and microbial protein synthesis. Ground FS replaced 0% or 15% of barley grain, along with VE at 0 or 1000 IU d−1 in a 2 × 2 factorial experiment. Flaxseed lowered neutral detergent fiber (P = 0.001) and acid detergent fiber (P = 0.01) and increased (P = 0.001) nitrogen (N) disappearance. Flaxseed also increased (P = 0.01) total volatile FA and decreased (P = 0.001) acetate production. When both FS and VE were included, the acetate:propionate ratio decreased (P = 0.04). Biohydrogenation of FA was not influenced by VE, but total FA and C18:0 in effluent were increased (P = 0.001) and C16:0 decreased (P = 0.001) by FS. With VE, total microbial N (MN) was increased (P = 0.001). In the concentrate, production of MN in feed-particle-bound bacteria was increased (P = 0.001) by VE. Vitamin E did not alter FA biohydrogenation but did promote MN production. The stable and relatively high pH in the Rusitec may have prevented the typical shift from C18:1 trans-11 to C18:1 trans-10 with concentrate diets. Future studies simulating subclinical acidosis in the Rusitec may illuminate ruminal mode(s) of action of VE on FA biohydrogenation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".