gMS-Classifier1 does not predict disability progression in multiple sclerosis
Bibliographic record
Abstract
Several clinical, immunological and radiological biomarkers have been shown to predict the disease course of multiple sclerosis (MS).One potential serum marker is the gMS-Classifier1, which is composed of IgM anti-Glc antibodies, namely anti-GAGA 2,3,4 and 6. Previous work demonstrated that the gMS-Classifier1 could not predict early conversion to clinically definite MS in a cohort of clinically isolated syndrome (CIS) patients, but predicted Expanded Disability Status Scale (EDSS) progression. Significance, however, was dependent on covariates, and confirmation in an independent study was required. The aim of this study was to test if the gMS-Classifier1 could predict early disability progression in a large multicenter cohort of patients with CIS or relapse-onset 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.012 |
| 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".