Technical note: Serum total protein and immunoglobulin G concentrations in neonatal dairy calves over the first 10 days of age
Bibliographic record
Abstract
Efficacy of passive transfer of immunity in young calves is commonly assessed using total serum protein (STP) or serum immunoglobulin G (IgG) concentration tested within the first few days of life. To our knowledge, no research has measured changes in these concentrations over this period to establish an appropriate age range for testing. The aim of this study was to monitor changes in STP and serum IgG concentrations from birth until 10 d of age to provide a basis for recommendations for when passive transfer of immunity in dairy calves can be measured. Concentrations of STP and IgG of 12 calves were measured at 11 time points: at approximately 30 min before colostrum feeding, at 24 h after colostrum feeding, and daily from d 2 to 10 of age. Mean (± standard deviation) STP and IgG concentrations were 4.61 ± 0.3 g/dL and 0.6 ± 0.6 mg/mL at birth, 5.83 ± 0.73 g/dL and 22.2 ± 9.6 mg/mL at 24 h after colostrum feeding, and 5.78 ± 0.52 g/dL and 16.1 ± 7.3 mg/mL at d 10 of age, respectively. The IgG concentration declined over subsequent days relative to IgG measured at 24 h at a rate of approximately 0.69 mg/mL per day, declining by 27.6 ± 6.2% (mean ± SD) on d 10. The concentration of STP did not decrease over time. Concentrations of IgG at 24 h after colostrum feeding were highly correlated with each of the measures of IgG over the 10-d period (r ≥0.97). These correlations were supported by the Bland-Altman plots of agreement between the 24-h sample and subsequent samples. Compared with the reference value at 24 h, STP concentrations were highly correlated on d 2 and 3 (r ≥0.98), highly correlated but variable from d 4 to 9 (r ≥0.88), and lower at d 10 (r = 0.76). These results indicate that calves may be reliably tested for passive transfer of immunity using IgG or STP concentrations up to 9 d 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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".