Effects of Feeding ACP® as a Bio-supplement to Ewes Pre- and Postpartum on Energy Profile and Offspring Growth Weight
Bibliographic record
Abstract
During the transition period in sheep, which consists of pre-partum and the beginning of lactation, the demands for glucose are extremely high and its absence or reduction causes several metabolic problems to arise leading to economic losses. Looking for alternative sources to growth promoters, sources of energy precursors of natural origin are being studied. This study aims to evaluate the effects and influence on plasma levels of Glucose, BHB and NEFA in pregnant ewes supplemented with coconut powder (ACP®) during the transition period. Two groups of ewes were used, totaling 13 animals of the Santa Inês breed that were supplemented with 30 g of powder coconut water (ACP) per day from 110 days before calving to 60 days after calving. Blood samples were taken on the day of delivery, 7, 21, 30 and 60 days after delivery. It was possible to observe that the test group (ACPg) remained stable with animals maintaining glucose levels without showing changes, even on the day of delivery, despite the fact that 80% of the ewes had twin births. The levels of BHB and NEFA were also better compared to the control group (Cg). The Cg showed greater instability throughout the experiment, with moments of hyper and hypoglycemia, BHB and NEFA also showed alterations. Lambs from ACPg showed better carcass growth compared to Cg. Therefore, the collection of results support the idea that, supplementation of ACP to pregnant ewes could be an important tool to reduce negative energy balance and offspring development in pregnant ewes.
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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) | 0.000 | 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 | 0.001 |
| 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".