Precision medicine in the multiple sclerosis clinic: Selecting the right patient for the right treatment
Bibliographic record
Abstract
Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system (CNS), affecting patients of all ages, causing neurologic disability if inadequately treated. Some patients have a relatively benign disease course without significant disability after decades, while a more aggressive course ensues in others and disability progression occurs after only several years. Certain risk factors confer a higher chance of a patient having aggressive MS. Currently over 15 disease-modifying treatments (DMTs) are approved for MS with different efficacy and safety profiles. Deciding which DMT to use in a specific patient requires a careful analysis of a patient's disease course for high-risk factors for early progression, consideration of the efficacy and safety profile for potential therapy, as well as understanding of a patient's lifestyle and expectations. The integration of these factors is the art of precision medicine, a necessary practice in the treatment of patients with MS.
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How this classification was reachedexpand
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".