The Effects of Feeding Deoxynivalenol-Contaminated, Low Complexity Diets to Nursery Pigs, with or without Immune-Modulating Feed Additives
Bibliographic record
Abstract
Pork producers operate under tight profit margins. Nursery diets are the most expensive in the pork production cycle. Therefore, this thesis investigated the use of low-complexity (LC) diets in the nursery and assessed the effects of deoxynivalenol (DON) contamination and the supplementation of a commercial feed additive or fish oil on pig growth performance, gut morphology, and immune response to assess application to industry. Growth performance was not different for pigs fed LC diets with no or low DON contamination than pigs fed the high-complexity diet as the same bodyweight was reached by the end of the nursery period. The commercial feed additive improved certain immune parameters and gut morphology when feeding high DON-contaminated diets but did not rescue growth performance. Therefore, low-complexity diets could be fed to nursery pigs so long as DON-contamination is below 1.5 ppm, and the commercial feed additive may improve immune function and gut morphology.
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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".