Effect of enhanced whole-milk feeding in calves on subsequent first-lactation performance
Bibliographic record
Abstract
The objective of this study was to determine the effect of enhanced whole-milk (WM) feeding systems in calves from birth to 8wk of age on subsequent first-lactation performance. The experiment was conducted as a completely randomized design consisting of 2 treatment groups. At birth, 152 Holstein heifer calves were randomly assigned to 1 of 2 treatments: (i) 4L of WM/d or (ii) 8L of WM/d. The calves were bucket fed 2 or 4L of WM twice daily at 0700 and 1600h. Each calf was housed individually in temperature-controlled nurseries and had ad libitum access to water and textured calf starter daily. Calves consumed greater volumes of textured calf starter when fed 4 versus 8L of WM/d. Water intakes mirrored starter intakes, leading to greater water consumption at weaning. Calves reared on 8L of WM/d were heavier at d 56 than calves reared on 4L of WM/d. The average daily gain of the calves offered 8L of WM/d from d 0 to 56 was greater than that of calves offered 4L of WM/d. Structural measurements were significantly greater for calves that consumed 8L of WM/d. The differences observed in withers height and live BW due to WM feeding level were not apparent by 3 and 12mo of age, respectively. Rumen pH was higher in calves that consumed 8L of WM/d than in calves that consumed 4L of WM/d. Whole-milk feeding level did not affect age at first calving or milk-production parameters. These results suggest that enhanced WM feeding improved growth performance until 3mo of age. However, first-lactation results indicated no lactation-performance benefits of increased nutrition and growth performance during the milk-fed period in dairy calves.
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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 | 0.001 |
| 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".