Effects of a silica-based feed supplement on performance, health, and litter quality of growing turkeys
Bibliographic record
Abstract
Poor litter quality is a potential challenge to footpad health as well as the primary cause of ammonia volatilization. High ambient ammonia concentration is one of the most significant factors negatively affecting poultry production today. Some minerals have been reported to reduce ammonia release from poultry litter. Silicon dioxide, a highly pure and natural mineral, shows promise in decreasing ammonia volatilization and improving litter quality. The objective of the current study was to investigate the effects of feed-borne silicon dioxide on litter quality and how this impacts bird performance, general health and footpad health throughout a 12-wk posthatching turkey study. Supplementing the diet with silicon dioxide was found to significantly improve turkey BW gain and the efficiency of feed conversion. The severity of footpad dermatitis was monitored throughout the experimental period but no significant effect of diet was seen. The feeding of silicon dioxide reduced litter pH which decreased the conversion of NH4⁺ to NH3 thereby reducing nitrogen losses from litter. It was concluded that, under our study conditions, the feeding of 0.02% silicon dioxide offers potential economic benefits to turkey producers.
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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".