Focal and diffuse cervical spinal cord damage in patients with early relapsing–remitting MS: A multicentre magnetisation transfer ratio study
Bibliographic record
Abstract
BACKGROUND: Studies including patients with well-established multiple sclerosis (MS) have shown a significant and disability-related reduction in the cervical spinal cord (SC) magnetisation transfer ratio (MTR). OBJECTIVES: The objectives are to (1) assess whether MTR reduction is already measurable in the SC of patients with early relapsing-remitting multiple sclerosis (RRMS) and (2) describe its spatial distribution. METHODS: We included 60 patients with RRMS <12 months and 34 age-matched controls at five centres. Axial T2*w, sagittal T2w, sagittal phase-sensitive inversion recovery (PSIR), 3DT1w, and axial magnetisation transfer (MT) images were acquired from C1 to C7. Lesions were manually labelled and mean MTR values computed both for the whole SC and for normal-appearing SC in different regions of interest. RESULTS: = 0.0003). We observed a greater mean reduction in MTR for vertebral levels displaying the highest lesion loads (C2-C4). In the axial plane, we observed a greater mean MTR reduction at the SC periphery and barycentre. CONCLUSION: Cervical SC tissue damage measured using MTR is not restricted to macroscopic lesions in patients with early RRMS and is not homogeneously distributed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".