Effects of red-osier dogwood extracts on growth performance, intestinal digestive and absorptive functions, and meat quality of broiler chickens
Bibliographic record
Abstract
A total of 320 one-day-old Cobb 500 chicks with an initial weight of 48.3 ± 3.3 g·pen−1 were assigned to four dietary treatments with eight replicates provided in three phases for 46 d. The treatments were fed as mash diets and included (1) negative control (NC) corn-soybean basal diet, (2) positive control (PC) basal diet with 30 ppm avilamycin, (3) basal diet supplemented with 1000 ppm red-osier dogwood extracts (RDE1), and (4) basal diet with 3000 ppm red-osier dogwood extracts (RDE2). Results showed reduced jejunal crypt depth in RDE1 and increased villus:crypt ratio in groups (either RDE1 or RDE2) (P < 0.05). Cationic amino acid (AA) transporter mRNA abundance was decreased (P < 0.05) in RDE1, RDE2, and PC treatments, but peptide and neutral AA transporter mRNA abundance were higher (P < 0.05) in RDE2 compared with NC. Apparent ileal digestibility of crude fat was increased in RDE2 and PC compared with NC, whereas AA digestibility was greater in RDE1, RDE2, and PC (P < 0.05). In conclusion, red-osier dogwood had no effect on growth performance, improved the intestinal health and function of broiler chickens, and had no detrimental effects on meat quality.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".