Boran calves reared under partial milk offtake can undergo compensatory growth post-weaning and optimize beef-milk productivity
Bibliographic record
Abstract
This study determined the long-term effect of restricted suckling on the post-weaning performance of Boran cattle. Thirty-two nursing cows and their calves arranged in a 4 X 2 factorial experiment were grazed in the tropical ecological zone IV range. The treatments were Full Suckling (FS), Milking from 1 Quarter (M1Q), milking from 2 Quarters (M2Q) and milking from 3 Quarters (M3Q) of the udder. Each treatment had eight calves, four of each sex. Weaning was at 210 days of age. At weaning, the M3Q calves had the lowest weight (P < 0.01), while the other treatments had similar weights. The highest (P < 0.01) post-weaning weight gains were during 18–24 months of age by M3Q treatment, which were 382 and 373 g/day for females (heifers) and males (steers), respectively. Steers from all treatments had similar weights from 12 months onwards while all the heifers reached the minimum mating weight set at 270 kg by 31 months. Their mating and calving were successful. The findings revealed that Boran calves can survive to weaning when suckling only a quarter (25%) of milk produced by dams yielding at least four litres daily. Upon weaning, compensatory growth occurs and enables catching up by 12–24 months of age.
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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 | 0.000 |
| 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".