Occurrence and pathology of cutaneous tumours in dogs
Bibliographic record
Abstract
<p style="text-align:justify">The current research work was undertaken to study the occurrence and pathology of cutaneous tumours in dogs and their age, breed, location and gender-wise distribution. A total of 33 samples suspected of cutaneous tumours were collected from the cases presented to Teaching Veterinary Clinical Complex (TVCC), Pookode, Wayanad, Kerala during a period of 12 months from June 2022 to June 2023. Based on histopathology, most of the tumours were diagnosed as benign. Majority of the tumours were of mesenchymal origin. Among different histological types, highest occurrence was that of squamous cell carcinoma (SCC) and trichoblastoma followed by histiocytoma, lipoma, mast cell tumour, hepatoid gland adenocarcinoma and haemangioma. Although, the incidence was higher among males and among the dogs belonging to the age group of 5-10 years, it was not statistically significant. Among different breeds, highest occurrence was observed in Labrador Retriever followed by German Shepherd. The study also warrants large scale epidemiological studies to identify the risk factors and to unravel the etiopathogenesis of canine cutaneous neoplasms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".