Combined carbon dioxide laser and cryosurgical ablation of rostral nasal septum squamous cell carcinoma in 10 dogs
Bibliographic record
Abstract
BACKGROUND: Squamous cell carcinoma (SCC) is the most commonly reported neoplasm of the nasal planum and treatment is focused on localized disease. Rostral maxillectomy and/or nasal planectomy are considered standard of care for excision of nasal planum SCC; however, the cosmetic outcome of these procedures can be deemed unacceptable by many pet owners. OBJECTIVES: ) laser surgery and cryosurgery as a palliative treatment modality in dogs with nasal SCCs. ANIMALS: Ten client-owned dogs with nasal SCC were included: seven neutered males, two spayed females and one intact male, with a median age of 12.5 years (range 9-15 years). METHODS AND MATERIALS: laser ablation was followed by cryosurgical ablation of the visible tumour, adjacent and subjacent tissue. Three rapid freeze-slow thaw cycles were performed. RESULTS: Eight of 10 dogs were Labrador retrievers. The ages ranged from 9 to 14 years. Overall median survival time was 260 days with two dogs still alive at the time of writing. CONCLUSIONS AND CLINICAL IMPORTANCE: laser and cryosurgical ablation was practical, cost-effective and provided an excellent aesthetic outcome in dogs with SCCs restricted to the nasal septum, while providing acceptable palliation of local disease.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".