Incidence and Histopathology of Sebaceous Gland Tumors in Dogs
Bibliographic record
Abstract
The study was aimed to know the prevalence of sebaceous gland tumor in canine and its classification based on histopathology. A total of 569 biopsy samples of canines suspected for neoplastic growth received by Department of Veterinary Pathology from TVCC departments of College of Veterinary Science and A.H. Anand over last 16 years (2001 to 2017) were analyzed. The biopsy samples were subjected to histopathological examinations by using H and E staining. Out of 569 biopsy samples, sebaceous gland growth was observed in 23 (4.04%) cases. The highest incidence (39.13%) was recorded for 9 to 12 years of age. The incidence of sebaceous gland tumor was observed in all the breeds; however, the Labrador retriever was the most affected breed followed by Pomeranian, non-descript and others. The frequent site for sebaceous gland tumor was eyelid. Out of 23 sebaceous gland tumors, one hyperplasia, 19 adenomas, two , and one adenocarcinoma were observed, suggesting that sebaceous gland adenoma was the most common type of sebaceous gland tumors in canine.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".