Performance of phytoncide (<i>Pinus koraiensis</i> extract) as an alternative to zinc oxide supplementation in weaning pig diet
Bibliographic record
Abstract
This study was implemented to assess the effect of Pinus koraiensis extract (PKE) compared with zinc oxide on growth performance, nutrient digestibility, blood profile, fecal bacterial count, and fecal gas emission of post-weaned pigs. This 6 wk experiment was divided into phase 1 (days 1–7), phase 2 (days 8–21), and phase 3 (days 22–42). A total of 150 crossbred weaning pigs (body weight; 10.14 ± 0.78 kg) were randomly sorted in five treatment diets (six replications per treatment; five pigs per pen) presented as CON, basal diet; ZnO, CON + 0.30% zinc oxide; PKE1, CON + 0.05% PKE; PKE2, CON + 0.10% PKE; and PKE3, CON + 0.15% PKE. Pinus koraiensis extract supplementation linearly reduced gain to feed ratio in all phases except phase 3. It also linearly increased average daily gain in the overall experiment compared with the CON group. The increasing level of PKE supplementation brought linear improvement in aspartate aminotransferase of blood profile. Escherichia coli bacterial count and NH 3 gas emission were decreased linearly by PKE supplementation in comparison to the CON diet. Though PKE supplementation did not show similar influence as ZnO, it showed beneficial results in weaning pigs’ growth, nutrient digestibility, fecal bacterial count, and reduction of fecal gas emission.
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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) | 0.001 | 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".