Prevalence of cutaneous and mucosal lesions in dairy cattle admitted to a Canadian Veterinary Teaching Hospital from 2018 to 2019
Bibliographic record
Abstract
BACKGROUND: The prevalence, anatomical distribution, or nature of cutaneous, hair and oral mucosal abnormalities (CHMAs) in cattle is uncertain. OBJECTIVES: To determine how often dairy cattle admitted to a veterinary teaching hospital (VTH) had CHMAs (except for foot and ear canal) on physical examination and if there was an age-related difference. ANIMALS: Four hundred and thirty-three cattle: cattle <3 months (n = 85), cattle 3 to 24 months (n = 73), and cattle >24 months (n = 275). METHODS: In this descriptive, observational, prospective study, CHMAs of dairy cattle admitted to the VTH of the Université de Montréal were recorded over 1 year. Prevalences were calculated. Dermatological examinations were performed within 48 hours of admission, according to a glossary. Chi-square tests were used to compare prevalence between age groups. RESULTS: The 433 cattle were mostly females (97.5%) and of the Holstein breed (89.8%). The prevalence of cattle <3 months presenting with at least 1 identifiable CHMA was 65% (55/85). In cattle 3 to 24 months old, it was 90% (66/73), and in cattle >24 months, it was 99.3% (273/275). There were significant differences (P < .001) between the prevalence of CHMAs localized on the ischia, ilia, stifles, hocks, carpi, flank, lateral neck, dorsal cervical, and cornual regions in cattle >24 months vs <3 months. CONCLUSIONS AND CLINICAL IMPORTANCE: CHMAs were highly prevalent and age-specific. Calluses on the carpi and hocks of cattle >24 months were the most common CHMAs.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".