A case of cutaneous mast cell tumor in a dog
Bibliographic record
Abstract
Cutaneous mast cell tumors comprise approximately 20% of cutaneous tumors in dogs. It is commonly seen as solitary nodules on the skin. A 14-year-old, male, labrador crossbreed dog was brought to the Istanbul University-Cerrahpaşa Veterinary Faculty internal medicine policlinic due to the formation of generalized nodules that started on the right hind leg and spread to the head, abdomen, scrotum and lateral thorax within a month. On physical examination, body temperature was 39,1°C, swelling in the submandibular lymph nodes, and widespread erythematous and nodular structures on the skin were observed. Hemogram and serum biochemistry analyzes were within normal ranges. Biopsies were taken from 0,5 – 0,6 cm diameter nodules in order to reach a definitive diagnosis of the patient who had not received any treatment before. Neoplastic mast cell accumulations with rounded morphology were observed in the dermis. Masitinib 12,5 mg/kg/day, PO (Masivet®) was administered to the patient who was diagnosed with Stage 2 cutaneous mast cell tumor according to Patnaik grading system. After 17 days of treatment, the patient showed significant clinical improvement. The disease relapsed after a 1-month break from the treatment. 15 mg/kg/day PO, Mastinib together with 1 mg/kg methylprednisolone (Prednol®) 1mg/kg PO were administered, but no regression was observed in the nodules. Due to severe lethargy, vomiting, anorexia, and spread of the masses, the patient was euthanized with the request of the owner. In our opinion, cutaneous mast cell tumors should be considered by clinician veterinarians in the evaluation of nodular skin diseases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".