Pediatric Inflammatory Diseases
Bibliographic record
Abstract
Central nervous system (CNS) vasculitis can affect both adults and children, but some of these occur almost exclusively in childhood. In children may develop as a primary condition or secondary to an underlying systemic disease. Cerebral vasculitis can be classified on the basis of the diameter of the involved vessels, although there is no univocal consensus. The diagnosis of CNS vasculitis is particularly difficult because the available investigative modalities have limited sensitivities and specificities. The most helpful diagnostic tests include cerebrospinal fluid analysis, MRI (MR angiography/venography (MRA/MRV) of the brain, and angiography. However, brain biopsy may be required to diagnose small vessel vasculitis in order to make differential diagnosis with a wide range of conditions, such as degenerative vasculopathies, embolic diseases, or coagulation disorders. This paper discusses on current understanding of most frequent primary and secondary central nervous system vasculitis in children in which are involved small vessel.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".