Primary Central Nervous System Angiitis in a 10-year-old Girl
Bibliographic record
Abstract
Primary angiitis of central nervous system (PACNS) is well reported, however its occurrence in the pediatric population is infrequent. We describe the clinical, neuroimaging and histopathological features of PACNS in a young girl. A ten year-old, previously healthy girl presented with a threeweek history of progressive left hemiparesis and facial weakness. Other findings included left hemineglect, impaired concentration and memory. She had no evidence of systemic disease. Head computed tomography (CT), with and without contrast, revealed no abnormalities. Magnetic resonance imaging (MRI) demonstrated multifocal, bilateral signal abnormalities within basal ganglia, thalami, right frontal cortex and subcortical white matter on T2 and FLAIR images. However, these areas did not show restricted diffusion on diffusion weighted imaging (DWI). Cerebral angiography revealed normal intracranial vessels (Figure 1). Neuroimaging, three weeks later, showed progression of these abnormalities. The areas of abnormal signal showed heterogeneous and nodular enhancement on gadolinium enhanced T1 weighted images (Figure 2). Rheumatologic, metabolic, prothrombotic and cerebral spinal fluid investigations were normal.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".