Smouldering disease in paediatric-onset multiple sclerosis
Bibliographic record
Abstract
Smouldering disease in multiple sclerosis (MS) refers to chronic central nervous system processes that occur beyond acute inflammation, driving long-term disability. Although current therapies effectively reduce relapse rates and MRI lesions, many individuals experience progression independent of relapse activity. While clinical progression is uncommon during childhood or adolescence, growing evidence suggests that subclinical progressive disease biology is already active even in this young age group, warranting early intervention to preserve function. Conventional MRI, while critical for diagnosis, lacks sensitivity for subtle damage. Advanced MRI techniques, including detection of chronic active lesions, global and focal brain damage, hold promise for early identification. Fluid biomarkers, such as neurofilament light chain and glial fibrillary acidic protein, provide non-invasive measures of neuroaxonal injury and ongoing chronic inflammation. This review summarises the role of MRI and fluid biomarkers in detecting smouldering disease in paediatric-onset MS and their application in supporting therapeutic decision-making.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".