Setting a research agenda for progressive multiple sclerosis: The International Collaborative on Progressive MS
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
Despite significant progress in the development of therapies for relapsing MS, progressive MS remains comparatively disappointing. Our objective, in this paper, is to review the current challenges in developing therapies for progressive MS and identify key priority areas for research. A collaborative was convened by volunteer and staff leaders from several MS societies with the mission to expedite the development of effective disease-modifying and symptom management therapies for progressive forms of multiple sclerosis. Through a series of scientific and strategic planning meetings, the collaborative identified and developed new perspectives on five key priority areas for research: experimental models, identification and validation of targets and repurposing opportunities, proof-of-concept clinical trial strategies, clinical outcome measures, and symptom management and rehabilitation. Our conclusions, tackling the impediments in developing therapies for progressive MS will require an integrated, multi-disciplinary approach to enable effective translation of research into therapies for progressive MS. Engagement of the MS research community through an international effort is needed to address and fund these research priorities with the ultimate goal of expediting the development of disease-modifying and symptom-relief treatments for progressive MS.
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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| 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