MSBase: an international, online registry and platform for collaborative outcomes research in multiple sclerosis
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
Observational cohort studies are a powerful tool to assess the long-term outcome in chronic diseases. This study design has been utilized in local and regional outcome studies in multiple sclerosis (MS) and has yielded invaluable epidemiological information. The World Wide Web now provides an excellent opportunity for an international, collaborative cohort study of MS outcomes. A web platform--MSBase--has been designed to collect prospective data on patients with MS. It is purely observational, enabling participating neurologists to contribute data on diagnosis, treatment and progress, to review anonymous aggregate data and to benchmark their patient population against other patient subsets or the entire dataset. MSBase facilitates collaborative research by allowing the online creation of investigator-initiated regional, national and international substudies. The registry aims to answer epidemiological questions that can only be addressed by prospective assessments of large patient cohorts. The registry is funded through the independent MSBase Foundation, and governed by an International Scientific Advisory Board. The MSBase Foundation commenced operations in July 2004 and since then, 22 neurologists from 11 countries have joined MSBase and are contributing 2400 patients to the total data pool.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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