Canine oral papillary squamous cell carcinoma with lymph node metastasis in a dog.
Bibliographic record
Abstract
Canine oral papillary squamous cell carcinoma is a rare subtype of squamous cell carcinoma with low metastatic potential. This report describes a 6-month-old intact male Labrador retriever dog with a 2.2 × 2.1-centimeter intraoral mass located in the gingiva between the 1st and 2nd right mandibular premolars. Computed tomography revealed an exophytic mass infiltrating the mandible and right mandibular gingiva without evidence of regional lymph node enlargement or distant metastasis. Histopathological evaluation confirmed canine oral papillary squamous cell carcinoma with metastasis to the right mandibular lymph node (surgically removed) and carboplatin was administered postoperatively. At 1404 d post-surgery, no local recurrence or distant metastasis were observed. To the best of the authors' knowledge, this is the first reported case of canine oral papillary squamous cell carcinoma metastasizing to the lymph nodes. The dog was treated with chemotherapy after surgery and had a good long-term prognosis. Key clinical message: Canine oral papillary squamous cell carcinoma has not been reported to metastasize and is usually treated locally with surgery or radiation therapy. However, as in the case reported herein, metastasis to the lymph nodes may occur. In such cases, accurate evaluation of metastasis, including lymph node excision biopsy, and chemotherapy may need to be considered.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 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".