Herd characteristics and cow-level factors associated with Prototheca mastitis on dairy farms in Ontario, Canada
Bibliographic record
Abstract
Prototheca spp. are algae that cause incurable acute or chronic mastitis in dairy cows. The aim of this case-control study was the identification of cow- and herd-level risk factors for this unusual mastitis pathogen. Aseptically collected composite milk samples from 2,428 milking cows in 23 case and 23 control herds were collected between January and May 2011. A questionnaire was administered to the producers, and cow-level production and demographic data were gathered. In 58 of 64 isolates, Prototheca spp. and Prototheca zopfii genotypes were differentiated using PCR and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. All isolates were identified as Prototheca zopfii genotype 2. The mean within-herd prevalence for Prototheca spp. was 5.1% (range 0.0-12.5%). Case herds had a significantly lower herd-level prevalence of Staphylococcus aureus and a higher prevalence of yeasts than did control herds. The final logistic regression model for herd-level risk factors included use of intramammary injections of a non-intramammary drug [odds ratio (OR) = 136.8], the number of different injectable antibiotic products being used (OR = 2.82), the use of any dry cow teat sealant (external OR = 80.0; internal OR = 34.2), and having treated 3 or more displaced abomasums in the last 12 mo OR = 44.7). The final logistic regression model for cow-level risk factors included second or greater lactation (OR = 4.40) and the logarithm of the lactation-average somatic cell count (OR = 2.99). Unsanitary or repeated intramammary infusions, antibiotic treatment, and off-label use of injectable drugs in the udder might promote Prototheca udder infection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".