Assessment of the mastitis situation in Canada
Bibliographic record
Abstract
The reason for initiation of the studies described in this thesis is that the Canadian Bovine Mastitis Research Network needed to acquire knowledge of the distribution of mastitis pathogens across Canada to before starting projects to improve the udder health status of the national dairy herd. The aims of this thesis were, therefore, to estimate: (1) the incidence rate of clinical mastitis (IRCM) and pathogen-specific IRCM per region on Canadian dairy farms and the association of pathogen-specific IRCM with bulk milk somatic cell count (BMSCC) and barn type; (2) associations of risk factors with overall and pathogen-specific IRCM on Canadian dairy farms; (3) the adoption proportion of recommended mastitis preventive management practices on Canadian dairy farms; (4) the herd-level prevalence of contagious mastitis pathogens; and (5) associations of certain management practices with the isolation of contagious mastitis pathogens from bulk tank milk. Overall mean IRCM was 22 cases per 100 cow-years in the selected herds. There was no association between BMSCC and overall IRCM, but Escherichia coli and culture-negative IRCM was highest in low and medium BMSCC herds. Herds in Ontario and Quebec had the highest IRCM, and herds in the Western provinces had the lowest IRCM. The most frequently isolated pathogens from clinical mastitis in Canada were Staphylococcus aureus, E. coli, Streptococcus uberis, and coagulase-negative staphylococci. Escherichia coli IRCM was relatively higher in Ontario than in other regions, but Streptococcus dysgalactiae IRCM was highest in Québec. Staphylococcus aureus is present in bulk tank milk of nearly all Canadian dairy farms, whereas Streptococcus agalactiae may be near extinction in Canada. Adoption of most of these recommended mastitis management practices is high in Canadian dairy herds. We demonstrated that season had an effect on all udder health parameters, BMSCC, individual cow somatic cell count (ICSCC), and IRCM. And finally, that quarter SCC fluctuates during and between milking which has consequences for implementing udder health programs that use lCSCC to identify cows with an intramammary infection. The Canadian mastitis control program should not only focus on reducing Staph. aureus and information transfer, but should also find ways to motivate producers to implement these practices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".