A randomized controlled trial on preweaning morbidity, growth and mortality in Holstein heifers fed a lacteal-derived colostrum replacer or pooled maternal colostrum
Bibliographic record
Abstract
BACKGROUND: The objective of this randomized controlled trial was to determine the effect of feeding a commercial lacteal-derived colostrum replacer (CR) or pooled maternal colostrum (MC) on preweaning morbidity, growth and mortality in Holstein heifer calves. A total of 568 calves were randomly assigned to be fed either 3.8 L of pooled MC or two doses (200 g IgG) of a CR. Calves were monitored daily for preweaning morbidity until weaning at 60 d old. Birth and weaning weights were measured to estimate growth rates. RESULTS: Calves fed CR were significantly less likely to be affected with a diarrhea event (OR = 0.58; 95% CI, 0.38 to 0.88; P value = 0.011) and had a higher rate of daily weight gain (0.051 kg/day; 95% CI, 0.03 to 0.08; P value <0.001) compared to calves fed pooled MC. Use of lacteal-derived colostrum replacer was not significantly associated with respiratory disease (OR = 1.01; 95% CI 0.67 to 1.51; P value = 0.974 ), omphalitis (OR = 0.93; 95% CI 0.06 to 14.86; P value = 0.956), or mortality (HR = 0.71; 95% CI 0.27 to 1.92; P value = 0.505) in the study calves. CONCLUSIONS: The lacteal-derived CR fed at the study dose was a viable colostrum alternative in the event of poor quality pooled MC for the prevention of preweaning diarrhea and resulted in higher growth rates in comparison to calves fed pooled MC in the study herd.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".