Environmental Stress in Chickens and the Potential Effectiveness of Dietary Vitamin Supplementation
Bibliographic record
Abstract
Environmental stressors can promote the vulnerability of animals to infections; it is therefore, essential to understand how stressors affect the immune system, the adaptive capacity of animals to respond, and effective techniques in managing stress. This review highlights scientific evidence regarding environmental stress challenge models and the potential effectiveness of vitamin supplementation. The major environmental stressors discussed are heat and cold stress, feed restriction, stocking density, and pollutants. Much work has been done to identify the effects of environmental stress in broilers and layers, while few involved other types of poultry. Studies indicated that chickens' performance, health, and welfare are compromised when challenged with environmental stress. These stressors result in physiological alterations, behavioral changes, decreased egg and meat quality, tissue and intestinal damage, and high mortalities. The application of vitamins with other nutritional approaches can help in combating these environmental stressors in chickens. Poultry birds do not synthesize sufficient vitamins during stressful periods. It is therefore suggested that chicken diets are supplemented with vitamins when subjected to environmental stress. Combination of vitamins are considered more efficient than the use of individual vitamins in alleviating environmental stress in chickens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".