Penetrating sclerokeratoplasty and autologous pinnal cartilage and conjunctival grafting to treat a large limbal melanoma in a dog
Bibliographic record
Abstract
A four-year-old neutered male Labrador retriever presented to Portland Veterinary Specialists Ophthalmology Service for evaluation of a pigmented mass oculus sinister (OS) of approximately 4-month duration. Complete ophthalmic examination revealed a large, pigmented, raised, well-demarcated, epibulbar mass appearing to originate from the nasodorsal limbal region. The mass was smooth and roughly circular, extending approximately 4 mm into the sclera and 14 mm into the nasodorsal cornea. Gonioscopy directly under the mass was not possible due to mass size. The visible iridocorneal angle was normal. High-resolution B-scan ultrasound showed mass extension to Descemet's membrane and deep sclera, but no intraocular invasion. Penetrating sclerokeratoplasty was performed followed by autologous pinnal cartilage and conjunctival grafting to repair the corneoscleral defect (20 mm x 19 mm) and to restore globe integrity and function. Histopathology confirmed the mass to be a benign limbal melanoma with complete excision. The surgery site healed without complication, and the pinnal cartilage became fully incorporated into the globe. Twelve months postoperatively, the patient remains visual with a normal intraocular and fundic examination. The pinnal harvest site on the right ear healed without complication. To the authors' knowledge, this is the first reported case of corneoscleral grafting using autologous pinnal cartilage. This may represent a viable alternative to other corneoscleral grafting procedures for large defects and is an attractive treatment option due to lack of host rejection, readily available source of donor cartilage, and provision of tectonic support to the globe.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".