Differences in udder health and immune response traits of Holstein-Friesians, Norwegian Reds, and their crosses in second lactation
Bibliographic record
Abstract
The objective of this study was to investigate potential differences in udder health and immune response traits among Holstein-Friesian (HF), Norwegian Red (NR), and NR x HF (NRX) cows on 30 commercial Irish dairy farms. A total of 648 second-lactation cows (HF n = 274, NR n = 207, and NRX n = 167) were immunized with hen egg white lysozyme (HEWL) to induce antibody-mediated immune response (AMIR). Candida albicans was used to induce a cell-mediated immune response, with in vivo delayed-type hypersensitivity used as the indicator. Antibody response to HEWL was measured by ELISA. Udder health defined as mean somatic cell score (SCS) over the lactation, mean SCS within 30 d of the beginning of the immunization, peak SCS for each individual cow during lactation, and incidence of mastitis were statistically superior for the NR. The NR had a greater primary AMIR, producing greater concentrations of anti-HEWL immunoglobulin G on d 14 compared with HF and NRX. No difference was observed among the breed groups in the magnitude of secondary AMIR (d 21 post-immunization) or cell-mediated immune response. The proportion of high and low responders was similar across breed groups. Cows with high AMIR and high cell-mediated immune response had significantly lower mean SCS within 30 d of the start of the immunization, but greater occurrence of clinical mastitis, recorded as a binary trait over the course of the lactation. Otherwise, no significant difference in udder health was evident between cows designated as high and low responders. Although differences in mean breed group SCS values were in line with group mean AMIR values, no association was found among the traits when correlated on an individual cow basis. Results highlight the superiority of the NR with regard to udder health and suggest that improvements to udder health may result from crossbreeding with the NR. However, the immune response traits investigated proved to be inconsistent indicators of udder health.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".