Chapter 10 Beta-glucans and beta-glucanase in animal nutrition, do we understand their full effects?
Bibliographic record
Abstract
Feeding barley to poultry and pigs has long been known to be affected by β-glucan found in grain cell walls. For poultry, the β-glucan effect can be negative because of high viscosity found in the digestive tract reducing nutrient digestibility and destabilising the resident microbiota. The effect in pigs is less because of lower digesta viscosity and an increased ability of small intestine bacteria to depolymerize β-glucan. Despite differences in the extent of the β-glucan effect, the use of exogenous β-glucanase effectively reduces or eliminates the negative effects and stabilizes the digestive tract microbiota. Despite this fundamental knowledge, research using humans, as well as in vitro models and other animal species, suggests that poultry and pigs might benefit from a more detailed understanding of β-glucan effects. Two areas with promise, particularly in a reduced or antibiotic free era, are positive effects of β-glucan on host immunity and the potential for β-glucan to serve as a prebiotic in animal feeds. Superimposed on this knowledge is the need to understand how exogenous β-glucanase can be used to produce hydrolysis products that optimize these areas.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.054 | 0.033 |
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".