Effects of dietary silicate levels on growth performance, nutrient digestibility, fecal microflora, odorous gas emissions, blood characteristics, and foot and mouth disease antibodies in weaning to finishing pigs
Bibliographic record
Abstract
The goal of this study was to investigate effects of different levels of silicate supplementation in weaning to finishing pigs. A total of 96 piglets [(Landrace × Yorkshire) × Duroc] with initial body weight of 11.30 ± 0.02 kg were used for 16 wk (six replicate pens with four pigs per pen). Dietary treatment consisted of 0% (CON), 0.1% (T1), 0.5% (T2), and 1.0% (T3) silicate in the basal diet. Inclusion of 0.1% dietary silicate increased (P < 0.05) body weight, average daily gain, and gain-to-feed ratio in 0–16 wk. In addition, inclusion of 0.1% dietary silicate increased (P < 0.05) crude protein digestibility in 8 and 16 wk, whereas it decreased (P < 0.05) Escherichia coli count and ammonia emissions throughout the study period. Additionally, inclusion of dietary silicate increased (linear, P < 0.05) white blood cell in 4 wk, whereas it increased (quadratic, P < 0.05) white blood cell counts in 8 and 16 wk. Blood urea nitrogen decreased (quadratic, P < 0.05), and lymphocyte and foot and mouth antibodies increased (quadratic, P < 0.05) when silicate level increased. In conclusion, supplementation of 0.1% silicate in the diet showed positive effects in weaning to finishing pigs.
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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 | 0.000 | 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".