Effect of passive transfer of immunity on growth performance of preweaned dairy calves.
Bibliographic record
Abstract
The primary objective of this observational study was to examine the association between passive transfer of immunity and growth performance in preweaning calves. A secondary objective was to evaluate the utility of a heart girth tape (HGT) to estimate body weight (BW) in preweaning calves. A total of 142 Holstein calves were enrolled in this study. Blood samples were collected 24 to 48 hours after birth and serum immunoglobulin G (IgG) concentration for each calf was measured by radial immunodiffusion assay. Calf BW was determined at birth, at 21 days, and at weaning using an electronic scale (ES) and HGT. A significant positive association was detected between serum IgG and both BW at 21 days and average daily gain (ADG) from 0 to 21 days of life. Additionally, ADG from 0 to 42 days of life showed a trend toward an improved rate of gain as IgG concentration increased. The Pearson correlation coefficient between BW obtained from ES and HGT was 0.81 at birth, 0.86 at 21 days, and 0.83 at weaning. The mean differences between BW obtained from ES and HGT were -3.1 kg at birth, -3.2 kg at 21 days, and -7.7 kg at weaning. In conclusion, serum IgG concentration in neonatal calves is an important contributing factor for the variation in growth performance of preweaning calves. The HGT can be used to estimate the BW of preweaning calves but has a tendency to overestimate weight, especially at weaning compared to birth and 21 days 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 | 0.003 |
| 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) | 0.000 | 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".