Hemoconcentration differs in neonatal dairy calves: Considerations for assessment of transfer of passive immunity
Bibliographic record
Abstract
Assessing transfer of passive immunity (TPI) is a critical management strategy to evaluate colostrum management and feeding; however, variability in hemoconcentration or serum or plasma volume in calves might influence TPI assessment. The objectives of this study were to (1) describe the variability in hemoconcentration as well as TPI in Holstein calves in New York State and (2) describe the effect of adjusting total protein (TP) for the degree of hemoconcentration by applying a sample average proportion of plasma in blood (PP) on TPI assessment. Records of TP and PP from 703 Holstein calves 1 to 9 d of age from 19 commercial dairy farms were analyzed. The PP was determined by centrifugation of microhematocrit tubes and serum and plasma TP was determined by digital refractometry. Transfer of passive immunity was categorized using unadjusted TP (uTP) as excellent = ≥6.2, good = 5.8-6.1, fair = 5.1-5.7, and poor <5.1 g/dL. Individual calf TP concentrations were adjusted to the sample average PP and TPI categories were reassessed using the adjusted TP value (aTP). The sample mean ± SD (range) PP was 68.8% ± 5.8% (50.5% to 86.0%). The PP was lower on d 1 compared with d 7 of age. Using uTP to categorize TPI, 22 (3.1%) calves had poor, 113 (16.2%) calves had fair, 164 (23.6%) calves had good, and 397 (57.1%) calves had excellent TPI, respectively. After adjusting TP for hemoconcentration, TPI determined using aTP resulted in 52 (7.5%, +4.4 percentage points) calves in poor, 137 (19.7%, +3.5 percentage points) calves in fair, 122 (17.5%, -6.1 percentage points) calves in good, and 385 (55.3%, -1.8 percentage points) calves in excellent. The mean (range) proportion of calves with TPI determined using uTP by farm was 3.9% (0% to 16%) for poor, 19.0% (2% to 36%) for fair, 25.3% (10% to 42%) for good, 51.8% (26% to 83%) for excellent. When categorized using aTP, the proportion of calves by farm was 8.1% (0% to 21%) in poor, 20.5% (8% to 42%) in fair, 19.1% (6% to 33%) in good, and 52.4% (27% to 83%) in excellent TPI. In conclusion, PP was variable in calves during the time of TPI assessment and this variability should be considered when assessing TPI at the calf- or herd level.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".