Comparative study of the effects of high- versus low-dose zinc oxide in the diet with or without probiotic supplementation on weaning pigs' growth performance, nutrient utilization, fecal microbes, noxious gas discharges, and fecal score
Bibliographic record
Abstract
This study was conducted to determine the effects of high- versus low-dose (3000 vs. 300) zinc oxide (ZnO) in combination with or without a probiotic complex (0.1%) on weaned piglet production efficiency, nutrient absorption, fecal bacterial counts, noxious gas emissions, and fecal score. A 42-day experiment included 180 crossbred weaned piglets [Duroc × (Yorkshire × Landrace); 28 days old; 6.61 ± 1.29 kg] and four dietary treatments. An HZ (high ZnO) diet increased body weight at week 6, average daily gain at week 3, week 6, and overall period, and gain-to-feed ratio (G:F) at week 3 compared with an LZ (low ZnO) diet. G:F tended to increase with the LZP (LZ with probiotic) diet compared with the HZP (HZ with probiotic) diet at week 1. Escherichia coli count decreased by HZ diet compared with the LZ diet. In addition, E. coli count decreased and Lactobacillus count increased with the HZP diet compared with the LZP diet. There was no effect of treatment on nutrient digestibility, noxious gas emission, and fecal score. No interactive effect was seen between ZnO and probiotic. Therefore, high-dose ZnO inclusion improved growth performance and probiotic addition improved fecal microbiota, but no synergistic effect was found from ZnO and probiotic complex interaction.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".