Incidence Rates of Clinical Mastitis among Canadian Holsteins Classified as High, Average, or Low Immune Responders
Bibliographic record
Abstract
The objective of this study was to compare the incidence rate of clinical mastitis (IRCM) between cows classified as high, average, or low for antibody-mediated immune responses (AMIR) and cell-mediated immune responses (CMIR). In collaboration with the Canadian Bovine Mastitis Research Network, 458 lactating Holsteins from 41 herds were immunized with a type 1 and a type 2 test antigen to stimulate adaptive immune responses. A delayed-type hypersensitivity test to the type 1 test antigen was used as an indicator of CMIR, and serum antibody of the IgG1 isotype to the type 2 test antigen was used for AMIR determination. By using estimated breeding values for these traits, cows were classified as high, average, or low responders. The IRCM was calculated as the number of cases of mastitis experienced over the total time at risk throughout the 2-year study period. High-AMIR cows had an IRCM of 17.1 cases per 100 cow-years, which was significantly lower than average and low responders, with 27.9 and 30.7 cases per 100 cow-years, respectively. Low-AMIR cows tended to have the most severe mastitis. No differences in the IRCM were noted when cows were classified based on CMIR, likely due to the extracellular nature of mastitis-causing pathogens. The results of this study demonstrate the desirability of breeding dairy cattle for enhanced immune responses to decrease the incidence and severity of mastitis in the Canadian dairy industry.
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How this classification was reachedexpand
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".