Intraocular malignant nerve sheath tumour in a brown eyed labrador retriever
Bibliographic record
Abstract
Abstract A 6‐year‐old, male, neutered, brown eyed labrador retriever was presented with an intraocular pale pink mass in the left eye. Enucleation of the globe was performed, and the mass was submitted for histopathology. Histology and immunohistochemistry confirmed the mass as a malignant nerve sheath tumour. There was no evidence of mass recurrence, and general and neurological examination remained normal at 9‐month follow‐up. While the majority of intraocular neoplasms are benign, a malignant neoplasm must be considered in all cases of intraocular mass. Differentiation between benign and malignant intraocular neoplasms is challenging and often requires enucleation with histopathology to confirm diagnosis. Tumour staging should be considered in the event of a malignant nerve sheath tumour. Finally, uveal malignant nerve sheath tumour should not only be considered in blue eyed dogs, but also in brown eyed dogs as in the present case.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".