A case of canine idiopathic eosinophilic meningoencephalitis with serial MRI scans, CSF analyses and histopathology
Bibliographic record
Abstract
A six‐year‐old labrador retriever mix was evaluated for behaviour change, hyperaesthesia and inappropriate urination. Neurological examination was consistent with a multifocal localisation. Multiple MRI scans, cerebrospinal fluid (CSF) analyses, infectious disease titres and a cerebral biopsy were performed over the course of nine months, confirming the diagnosis of idiopathic eosinophilic meningoencephalitis. The patient was treated with immunomodulatory medications, antibiotics, anthelminthics and anticonvulsant medications. Resolution of meningoencephalitis was achieved; however, permanent neurological deficits remained and seizures became more difficult to control. The patient’s neurological status was followed until her death approximately six years following initial presentation. This is the first and only reported case of idiopathic eosinophilic meningoencephalitis to have had multiple MRI scans and CSF analyses performed. This report allows for visual tracking of disease progression and correlates it with CSF characteristics and clinical signs. Furthermore, this report demonstrates the persistent long‐term ramifications of the disease, even after successful treatment.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".