Supplemental effect of coated refined fish oil on the performance of finishing pigs fed diets containing soybean meal as a partial alternative to barley or wheat feed ingredient
Bibliographic record
Abstract
A total of 195 finishing pigs with an average body weight (BW) of 78.65 ± 0.09 kg were assigned to one of three dietary treatments in a 28-d trial. The designated nutritional diets were as follows: CON; TRT1, CON + 0.2% coated refined fish oil; and TRT2, CON + 10% barley + 0.2% coated refined fish oil. The inclusion of coated refined fish oil with the barley-based diet significantly increased BW, average daily gain, and feed conversion ratio of finishing pigs throughout the experimental period. At the end of the experiment, pigs fed coated refined fish oil with the barley-based diet showed a significant improvement on nutrient digestibility of dry matter and nitrogen. Moreover, gas emission of NH3 and H2S concentration were significantly reduced. Also, drip loss during days 5 and 7 was significantly decreased in meat quality analysis of pigs fed coated refined fish oil supplemented to a barley-based diet. Furthermore, dietary coated refined fish oil with barley-based diet had significantly increased fatty acid profile of belly meat and reduced belly fat. In summary, the inclusion of coated refined fish oil with barley diet positively impacts on growth performance and nutritional values of meat quality in finishing 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 | 0.000 | 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".