Supplemental effect of xylanase on the growth performance, nutrient digestibility, and fecal score in weaned pigs
Bibliographic record
Abstract
A total of 208 weaned pigs were assigned to one of four dietary treatments according to their body weight and sex in a randomized complete block design. Each treatment consisted of 13 replicates with four pigs per pen. Dietary treatments were as follows: CON, Basal diet; TRT1, Basal diet + xylanase 900 U/kg feed; TRT2, Basal diet + xylanase 1800 U/kg feed; TRT3, Basal diet + xylanase 3600 U/kg feed. A linear improvement in body weight and average daily gain was observed at the end of weeks 3, 6, and overall, but there was no effect on average daily feed intake and feed efficacy during the trial period in which pigs fed 900, 1800, or 3600 U/kg xylanase. At week 6, digestibility of dry matter was linearly increased in pigs fed a diet containing the 3600 U/kg level of xylanase supplements, but there were no improvements observed in digestibility of nitrogen and energy throughout the trial. Moreover, no linear effects were observed on weaned pigs’ fecal scores during weeks 1, 3, and 6. In summary, incorporating graded levels of xylanase into the diets of weaned pigs can improve their growth performance and nutrient digestibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 | 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".