Imaging Pediatric Multiple Sclerosis—Challenges and Recent Advances
Bibliographic record
Abstract
Pediatric onset multiple sclerosis (POMS) is a rare disease with an incidence of 0.07 to 2.9/100'000 children per year. It follows a relapsing-remitting disease course and is characterized by rapid accrual of inflammatory lesions, high relapse frequency, and early cognitive impairment. Magnetic resonance imaging (MRI) plays a pivotal role in the diagnosis of POMS, and in the exclusion of other disorders mimicking POMS. Furthermore, MRI aids in disease monitoring, and in the evaluation of therapeutic efficacy in both clinical practice and clinical trials. Volumetric MRI studies, diffusion tensor imaging, resting-state, and task-based functional MRI provide deeper insight into the impact of POMS on maturing neural networks. This review article aims to highlight the importance of MRI in the care of POMS patients and to provide an overview on the different MRI techniques used in the management of POMS.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".