Formulating Diets for Improved Health Status of Pigs: Current Knowledge and Perspectives
Bibliographic record
Abstract
Our understanding of nutrition has been evolving to support both performance and immune status of pigs, particularly in disease-challenged animals which experience repartitioning of nutrients from growth towards the immune response. In this sense, it is critical to understand how stress may impact nutrient metabolism and the effects of nutritional interventions able to modulate organ (e.g., gastrointestinal tract) functionality and health. This will be pivotal in the development of effective diet formulation strategies in the context of improved animal performance and health. Therefore, this review will address qualitative and quantitative effects of immune system stimulation on voluntary feed intake and growth performance measurements in pigs. Due to the known repartitioning of nutrients, the effects of stimulating the immune system on nutrient requirements, stratified according to different challenge models, will be explored. Finally, different nutritional strategies (i.e., low protein, amino acid-supplemented diets; functional amino acid supplementation; dietary fiber level and source; diet complexity; organic acids; plant secondary metabolites) will be presented and discussed in the context of their possible role in enhancing the immune response and animal performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".