PSII-18 Impact of <i>Saccharomyces Cerevisiae Boulardii</i> Supplementation on Nursery Pig Performance
Bibliographic record
Abstract
Abstract Nine hundred newly-weaned pigs (PIC) with average body weight of 6.2 ± 0.1 kg were used in a 43d nursery study to evaluate the effect of a live yeast, Saccharomyces cerevisiae boulardii (Levucell SB Advantage, Elanco; LEV), on growth performance of nursery pigs. Each pen within a pen location-block was assigned to 1 of 3 treatments consisting of: 1) a control diet (CON) containing pharmacological levels of Zn (2,500 and 1,500 ppm in phase 1 and 2, respectively) and Cu (200 ppm for all phases), 2) CON with LEV at 0.1% (phase 1) and 0.05% (phase 2-3), and 3) CON but with 150 ppm Zn (phase 1-3) and 22 ppm Cu (phase 1-3). Feeding program consisted of a 3-phase feed budget (3, 6, 20 kg for phases 1, 2, and 3, respectively). Body weight (BW), average daily gain (ADG), average daily feed intake (ADFI), gain to feed (G:F), and end weight variation (EWV) were all analyzed using MIXED procedure in SAS using RCBD with treatment, pen location-block and initial BW as covariate. Dietary supplementation of nursery diets with LEV in the presence of high Zn and Cu increased final BW (P < 0.05, +1.3 kg), overall ADG (P < 0.05, +8%), and G:F (P< 0.05, +6%) compared with the control diet containing high Zn and Cu. There was no impact on other parameters (ADFI and EWV). Addition of LEV to low Zn and Cu diet supported the same level of performance (ADG, ADFI, G:F) as the control diet. The results of this study demonstrate growth performance enhancement when using Saccharomyces cerevisiae boulardii in nursery diets.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".