Dominant perivenular enhancement of tumefactive demyelinating lesions in multiple sclerosis
Bibliographic record
Abstract
Dominant perivenular enhancement of tumefactive demyelinating lesions in multiple sclerosisA 51-year-old woman presented with aphasia and bifrontal MRI lesions with punctuate and vague linear enhancement (figure).She improved spontaneously but 4 months later deteriorated due to the large mass and required cranial decompression.Innumerable, perivenular enhancements perpendicular to the lateral ventricles were seen within extensive bihemispheric white matter lesions.Multiple sclerosis (MS) was diagnosed based on typical inflammatory demyelination at biopsy, CSF oligoclonal bands, and a previous CNS event.Treatment with mitoxantrone and Copaxone followed.MRI lesions improved rapidly.She remains stable with minimal deficit (Expanded Disability Status Scale 1.0) 2 years later.Dominant perivenular enhancements are atypical for MS 1,2 but deserve recognition, although they may not prevent biopsy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".