Prevalence of intramammary infection in Dutch dairy herds
Bibliographic record
Abstract
A survey was carried out in 2003 in 49 dairy herds to determine the overall and pathogen-specific prevalence of intramammary infection (IMI) in Dutch dairy herds, and to compare the distribution with four studies performed from 1973 to 1985 in The Netherlands. Herds were randomly selected stratified over the 12 Dutch provinces, had at least 40 lactating cows and participated in the Dutch milk recording system. Quarter milk samples were collected from all 408 cows with a somatic cell count (SCC) >or=250,000 cells/ml and 145 heifers with SCC >or=150,000 cells/ml at the last milk test before the farm visit. Additionally, samples were collected from 519 (approximately 25%) of the remaining low-SCC cows and heifers with a SCC at the last milk test before the farm visit of <250 000 and <150 000 cells/ml, respectively. Bacterial growth occurred in 37.3% of milk samples of high-SCC cows and in 21.1% of low-SCC cows. Coagulase-negative staphylococci (CNS) were the most frequently isolated group of bacteria (10.8% of quarters) and were found in all herds. Prevalence of Staphylococcus aureus IMI was lower in 2003 than in 1973, respectively 1.8% and 6.2% of quarters. Prevalence of Streptococcus uberis and Str. dysgalactiae IMI was almost the same in the five samplings during the 30-year period, at 1.1-1.7 and 0.9-1.5%, respectively. Str. agalactiae was not found in this study. Prevalence of CNS IMI was higher in lactating heifers, while prevalence of Str. uberis, Str. dysgalactiae and penicillin-resistant Staph. aureus IMI was higher in older cows. Because distribution of pathogens changes over time, herd-level samples for bacteriological culturing must be taken regularly to monitor udder health. Additionally, national mastitis prevalence studies give important information through monitoring the national udder health status.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".