Nonruminant Nutrition symposium on natural phytobiotics for health of young animals and poultry: Mechanisms and application1,2
Bibliographic record
Abstract
Newly weaned piglets and young poultry are highly susceptible to various stressors, such as bacterial diseases resulting in decreased growth and even death (Lecce, 1986; Hoerr, 1998). Supplementing antibiotics in swine and poultry diets at subtherapeutic levels has long been shown to increase the growth rate (Becker et al., 1955; Stahly et al., 1980; Cromwell, 2002). However, due to growing concerns over antibiotic resistance, the use of antibiotics as growth promoters in animal diets could be limited due to public or regulatory pressures. Thus, current research involving feed additives for diets of young animals is focused on searching for alternatives to antibiotics that would have at least similar growth-promoting effects of antibiotics without causing bacterial resistance. Phytobiotics is a term used to describe plant-derived natural bioactive compounds, which affect animal growth and health, and is often applied to essential oils, botanicals, and extracts derived from herbal plants. Some phytobiotics are known to have antimicrobial or antiviral activities (Sökmen et al., 2004; Piao et al., 2006; Friedman, 2007). Those selected herbs or phytobiotics have long been used as complementary or alternative medicine to improve human health or to cure human disease. Recent advances in science have allowed for the identification of active components from selected phytobiotics and investigation into the mechanisms of those components in the animal's body. More recently, animal nutritionists have attempted to use some phytobiotics as alternatives to the use of antibiotics for young animals and birds (Mao et al., 2005; Kommera et al., 2006; Peeters et al., 2006; Yuan et al., 2006). However, results have been somewhat inconclusive with limited resources and understanding.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".