Effect of daily feeding frequency on performance of 2- to 4-month-old weaned dairy calves
Bibliographic record
Abstract
Ninety-six Holstein calves, 48 per treatment (in 12 pens of 4 calves per pen), were fed the same diet either once or 3 times daily for 56 d. The textured diet (corn, oats, protein supplement pellet) was blended with 5% chopped grass hay. Calves fed once daily were fed at 1100 h. Calves fed 3 times daily were fed 25% of daily allotment at 0600 h, 25% of the daily allotment at 1100 h, and 50% of the daily allotment at 1600 h. Diets and water were fed free choice. The trial was conducted with 2 blocks of 56 d with 48 calves per block. The average ambient temperature was 17°C. Calves were initially 2 mo old and 78 ± 1.7 kg. Calves were weighed, scored for body condition, and hip widths were measured initially and at 28 and 56 d. Body condition score was a 5-point system (1 being thin and 5 being obese). The 2 treatments were analyzed as a randomized complete block design with repeated measurements over time. Levene's test was used to test variability of intake and ADG. Pen was the experimental unit. No measurements differed (P > 0.05) between treatments. Body weight, ADG, DMI, and feed efficiency averaged 108 ± 2.1 kg, 1.06 ± 0.026 kg/d, 2.96 ± 0.049% of BW, and 0.33 ± 0.011 G:F, respectively. Feeding once daily is adequate for dairy calves between 2 and 4 mo 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".