Effects of nucleotide supplementation to corn–soybean meal-based diet on growth performance, fecal microflora, and blood profiles of sows and performance of suckling piglets
Bibliographic record
Abstract
A total of 45 sows (Landrace × Yorkshire) and their litters were used in this study to evaluate the efficacy of nucleotide supplementation on reproductive performance, growth performance, fecal microflora, and blood profiles in sows and piglets. Sows were allocated to one of three treatments (15 pigs per treatment and the average parity was 4.13). Dietary treatments consisted of (1) CON: basal diet, (2) T1: CON + 0.5% nucleotides, and (3) T2: CON + 1.0% nucleotides. In this study, the average daily feed intake during lactation and back fat at weaning day was increased linearly (P < 0.05) in sows with the increase in nucleotide supplementation levels. Sows receiving increasing levels of nucleotides had linearly increased fecal Lactobacillus counts and decreased Escherichia coli counts at weaning day (P < 0.05). Linear reduction of the epinephrine, norepinephrine, and cortisol in sows was observed at weaning day, whereas superoxide dismutase was increased linearly (P < 0.05). Body weight and average daily gain in piglets were linearly (P < 0.05) increased with the increasing levels of nucleotides. Linear increase (P < 0.05) was also observed on total piglets born, live piglets, and piglet survival. The current study demonstrated the importance of nucleotides in the diets of sows to improve sow and piglet performance.
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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".