Effects of butyrate supplementation in antibiotic‐free milk replacer and starter on growth performance in suckling calves
Bibliographic record
Abstract
Abstract The aim of this study was to evaluate butyrate supplementation of antibiotic‐free milk replacer and starter on growth performance in male Holstein calves. Twenty‐nine calves were divided into two groups. Group C (n = 13) was fed antibiotic‐free milk replacer without supplementation, and Group B (n = 16) was fed antibiotic‐free milk replacer supplemented with butyrate (1.6 % DM of Gustor BP70®). Starter in Group B contained 0.3 % DM of Gustor BP70®. The intake of milk replacer was lower in group B than in C (p = 0.07 for the treatment x week interaction). Body weight (BW) and heart girth (HG) in group B was higher than in C during the experimental period (p = 0.07 and 0.01 for the treatment × week interaction, respectively). The duration of the weaning period in group B was shorter than in group C (p = 0.02). β‐hydroxybutyrate (BHBA) was higher in group B than in C (p = 0.04). Insulin like growth factor‐1 (IGF‐1) concentrations tended to be higher in group B than in C (p = 0.07 for treatment × week interaction). Our results show that butyrate supplementation in antibiotic‐free milk replacer and starter exerted positive effects on growth performance in suckling calves.
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) | 0.001 | 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 | 0.000 |
| 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".