Imaging Pediatric Multiple Sclerosis—Challenges and Recent Advances
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it