Diagnosis of lymphoma based on magnetic resonance imaging, analysis of cerebrospinal fluid, intraocular fluid and fine‐needle aspirate of a uveal mass lesion in a dog
Bibliographic record
Abstract
Abstract A 10.5‐year‐old, male, entire labrador retriever dog was presented for chronic progressive ataxia and recent onset of a left‐sided head tilt and salivation. Neurological examination findings were deemed consistent with a multifocal brain and spinal cord neuroanatomic localisation. Ophthalmological examination of the right eye revealed pupil shape abnormality (dyscoria), a pale uveal mass lesion and white cellular sediment in the anterior chamber. Magnetic resonance imaging of the brain, eyes, thoracolumbar and lumbosacral spinal cord and surrounding structures showed multiple lesions affecting the central nervous system (brain), peripheral nervous system (left trigeminal nerve) and right eye. Cerebrospinal fluid, right eye anterior chamber fluid and fine‐needle aspirate biopsy of the uveal mass lesion yielded a cytological diagnosis of lymphoma (suspected large granular lymphocytic). The dog was discharged with palliative treatment and euthanased at home 4 days later. This case report documents the cytological diagnosis of lymphoma in the cerebrospinal fluid, intraocular fluid and fine‐needle aspirate of a uveal mass in a dog.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".