Review Article Childhood multiple sclerosis
Bibliographic record
Abstract
Abstract. Childhood multiple sclerosis (MS) is a rare demyelinating autoimmune disease with different risk factors and clinical features than adult onset MS. Onset of MS is extremely uncommon in early childhood, particularly in those less than 10 years of age. The overall prevalence of MS varies significantly from 1–10 in 100,000 people in Japan to 248 in 100,000 in Canada. At least 5 % of all MS patients have their first attack before 16 years of age with a female to male ratio of 1.4:1. Overall, childhood MS is being increasingly recognized. In this paper, an updated overview of childhood MS will be presented in the context of the available literature and our experience. Research into the earliest events in MS pathogenesis is needed to enhance our information of this disease. As well, understanding the triggers and initial immunologic targets involved may lead to the development of new therapies. Prospective longitudinal studies are required to evaluate the physical, cognitive, and psychosocial impact of childhood MS and the long term benefit of various therapeutic modalities.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".