EFNS guidelines on the use of neuroimaging in the management of multiple sclerosis
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
Magnetic resonance (MR)-based techniques are widely used for the assessment of patients with suspected and definite multiple sclerosis (MS). However, despite the publication of several position papers, which attempted to define the utility of MR techniques in the management of MS, their application in everyday clinical practice is still suboptimal. This is probably related, not only, to the fact that the majority of published guidelines focused on the optimization of MR technology in clinical trials, but also to the continuing development of modern, quantitative MR-based techniques, that have not as yet entered the clinical arena. The present report summarizes the conclusions of the 'EFNS Expert Panel of Neuroimaging of MS' on the application of conventional and non-conventional MR techniques to the clinical management of patients with MS. These guidelines are intended to assist in the use of conventional MRI for the diagnosis and longitudinal monitoring of patients with MS. In addition, they should provide a foundation for the development of more widespread but rational clinical applications of non-conventional MR-based techniques in studies of MS patients.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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