Treatment Optimization in Multiple Sclerosis: Canadian MS Working Group Recommendations
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
The Canadian Multiple Sclerosis Working Group has updated its treatment optimization recommendations (TORs) on the optimal use of disease-modifying therapies for patients with all forms of multiple sclerosis (MS). Recommendations provide guidance on initiating effective treatment early in the course of disease, monitoring response to therapy, and modifying or switching therapies to optimize disease control. The current TORs also address the treatment of pediatric MS, progressive MS and the identification and treatment of aggressive forms of the disease. Newer therapies offer improved efficacy, but also have potential safety concerns that must be adequately balanced, notably when treatment sequencing is considered. There are added discussions regarding the management of pregnancy, the future potential of biomarkers and consideration as to when it may be prudent to stop therapy. These TORs are meant to be used and interpreted by all neurologists with a special interest in the management of 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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