The relationship between cerebellar volume, clinical disability and cognitive changes in multiple sclerosis patients
Bibliographic record
Abstract
Background & Objective: Multiple Sclerosis (MS) is an inflammatory, demyelinating and degenerative disease of the central nervous system. To determine the extent of disability and loss of functions, we used the Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk Test (T25-FW), 9-Hole Peg Test (9-HFT), Symbol Digit Modalities test (SDMT) and the Montreal Cognitive Assessment Test (MOCA). In this study, we focused on the effects of cerebellar volume and the correlation between cerebellar atrophy and functional test results. Methods: We retrospectively recruited 58 MS patients and 30 healthy controls. Cranial magnetic resonance imaging (MRI) and functional tests were obtained from all subjects. Duration between clinical tests and MRI acquisition was no longer than two weeks. Volumetric MRI evaluation was performed with the volBrain automatic segmentation pipeline. Results were analyzed by t-test and Spearman correlation analysis to determine the relationship between variables and to compare the two groups. Results: Mean values for age (p=0.351) and distribution in gender (p=0.8.34) were similar for patients and controls. Mean disease duration in patients was 5.85 +/- 5.45 years. Mean values for cerebellar volume and normalized cerebellar volume were significantly reduced in patients compared to controls (p=0.036 and p=0.022, respectively). Cerebellar volumes were significantly correlated with the results of the SDMT, MOCA and timed T25-FW tests.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".