Improving passive transfer of immunoglobulins in calves. I: Dose effect of feeding a commercial colostrum replacer
Why this work is in the frame
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Bibliographic record
Abstract
The objective of this study was to describe the effects of feeding 1 or 2 doses of a commercially available colostrum-derived colostrum replacer (CR) on passive transfer of immunoglobulins (Ig) in newborn dairy calves, including IgG, IgG1, IgG2, IgA, and IgM. Newborn calves were removed from the dam before suckling and randomly assigned to 1 of 3 treatment groups: group 1 were fed 1 package (100 g of IgG) of CR product, group 2 was fed 2 packages (200 g of IgG) of the same CR product, and group 3 was fed 3.8 L of maternal colostrum. All colostrum treatments were fed using an esophageal tube feeder within 2 h of birth. Blood samples collected before colostrum feeding and at 24 h of age were tested for serum total protein and Ig concentrations. Mean 24-h serum total protein (TP) and IgG concentrations were significantly lower for calves in group 1 (n = 24; TP = 4.9 g/dL, IgG = 9.6 mg/mL) compared with calves in groups 2 or 3. There was no difference in 24-h serum TP or IgG concentrations between calves in group 2 (n = 23; TP = 5.5 g/dL, IgG = 19.0 mg/mL) and calves in group 3 (n = 22; TP = 5.7 g/dL, IgG = 20.7 mg/mL). Fifty-four, 100, and 91% of calves in groups 1, 2 and 3 achieved acceptable passive transfer (24-h serum IgG > or =10 mg/mL), respectively. Statistically significant but numerically small differences existed between calves in groups 2 and 3 for some 24-h serum Ig classes and subclasses (mean serum concentrations of IgG2, IgA, IgM) and for the relative percentages of Ig classes and subclasses (IgA, IgM, and IgG as a percentage of total Ig; IgG1 and IgG2 as a percentage of total IgG).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it