Effects of extracted rice bran supplementation on growth performance, nutrient digestibility, diarrhea score, blood profiles, and fecal microbial shedding in comparison with apramycin (antibiotic growth promoter) in weanling pigs
Bibliographic record
Abstract
This study evaluated the efficacy of extracted rice bran (ERB) in weanling piglets. One hundred forty weanling pigs [(Yorkshire × Landrace) × Duroc] with an average BW of 5.70 ± 1.41 kg (21 d of age) were fed in two phases in a 6-wk experiment. Weanling pigs were allotted to diets containing 0 or 0.1 g kg−1 of ERB, and 0 or 165 mg kg−1 of apramycin according to a 2 × 2 factorial arrangement of treatments. Both apramycin and ERB supplementation increased growth efficiency (G:F) during phase 1 and overall, respectively (P < 0.05). The apparent total tract digestibility (ATTD) of dry matter (DM) was increased in response to either ERB or apramycin at wk 2 and 6 (P < 0.05). Supplementation of ERB decreased total cholesterol (TC) and increased high-density lipoprotein cholesterol (HDL-C) in diets lacking ERB at wk 6 (P < 0.05). Pigs receiving diets supplemented with apramycin reduced Escherichia coli at wk 2 and 6, and Salmonella counts at wk 6 (P < 0.05). Supplementation of ERB increased fecal Lactobacillus and reduced Salmonella counts at wk 6 (P < 0.05). In conclusion, results indicated that dietary supplementation of ERB improved performance in weanling 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) | 0.001 | 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".