Epidemiological Study of Canine Mast Cell Tumours According to the Histological Malignancy Grade
Bibliographic record
Abstract
The aim of the study was to identify significant relationships between the tumour malignancy grade and dogs' age, breed, sex, size, and location of mast cell tumours (MCTs). MCTs accounted for 13.27% of all diagnosed canine skin tumours. The highest incidence was recorded among Boxers, Labrador Retrievers, American Staffordshire Terriers, and Golden Retrievers. Statistical analysis revealed significantly higher probability of occurrence of the grade I mast cell tumour in the French Bulldog in the head, neck, torso, and limb regions, the grade-II mast cell tumour in Boxer, Doberman, Dachshund, shepherds, and setters in the scrotal region, and the grade III mast cell tumour in Shar-Pei in the axilla region. In the group of the oldest dogs aged 11-16, there was higher risk of development of MCTs grade II and III. Young dogs (aged 2-3 and 4-6) were found to be more prone to development of MCTs grade I. There was no correlation between MCTs grade and dogs' sex and size. To the authors' knowledge this is the first report on statistical relationships between the degree of mast cell tumour malignancy and dogs' phenotypic traits, age and tumour location. This analysis indicate predilections for development of the particular mast cell tumour malignancy degrees in certain dog breeds, age, and anatomical location.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".