Effects of partial replacement of fishmeal with dried porcine soluble on the growth performance, nutrient digestibility, fecal microbiota, and fecal score in weaning pig
Bibliographic record
Abstract
Dried porcine solubles (DPSs) are the by-product obtained during the extraction of heparin from the porcine mucosa of the small intestine. The effects of partially replacing fishmeal with DPS in weaning pig diets on growth performance, nutrient digestibility, fecal microbial count, and fecal score were investigated here. A total of 70 crossbred ((Yorkshire × Landrace) × Duroc) weaning pigs were divided into two dietary treatment groups: dietary treatments, CON: 3% fishmeal; DPS: 1.5% fishmeal and 1.5% DPSs. Average daily gain was tended to increase ( p < 0.10) in weaning pigs fed DPS compared to the CON group in week 2. The digestibility of dry matter was tended to improve ( p < 0.10) in weaning pigs fed DPS diet group in week 2 and week 5. Fecal Lactobacillus count was tended to increase ( p < 0.10) and Escherichia coli was tended to decrease ( p < 0.10) in weaning pigs fed DPSs compared to the weaning pigs fed CON at week 5 of the feeding trial. Our findings suggest that partially replacing fishmeal with DPSs in weaning pig diets can have beneficial effects on the growth performance through the tendency to improve dry matter digestibility and fecal microbiota.
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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 | 0.000 | 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".