Bibliographic record
Abstract
A high-grade mast cell tumor of the conjunctiva in the Golden Retriever is a rare condition. Wide excisional conjunctival mass biopsy is suggested, combined with chemotherapy. A 9-year-old neutered female Golden Retriever with a painless conjunctival mass at the right temporal bulbar conjunctiva was presented at the Ophthalmology Clinic of the Small Animal Teaching Hospital, Faculty of Veterinary Sciences, Chulalongkorn University. Complete physical and ophthalmic examinations were performed. The metastasis of the primary conjunctival mass was investigated by radiography of the skull, orbit, thorax, and abdomen, as well as by ultrasonography in the orbit and abdomen. No metastasis was confirmed by imaging diagnosis. A wide excisional conjunctival mass biopsy was performed under general anesthesia. The histopathological study was conducted by a veterinary pathologist, who reported a high-grade mast cell tumor. Chemotherapy was prescribed for the dog. However, the dog died three weeks after surgical treatment due to an unknown cause, with no recurrence of the conjunctival mass. This case presents the atypical nature of conjunctival mast cell tumors in Golden Retrievers, emphasizing the need for individualized and concerned clinical management to improve results in predisposed breeds.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".