The Visuospatial Episodic Memory in Persian-speakingPatients with Multiple Sclerosis
Bibliographic record
Abstract
Background and purpose: Memory dysfunction is one the most common challenges of patients with Multiple Sclerosis (MS). Memory has a major role in daily life and influences social communication of individuals. The aim of this research was to investigate the function of nonverbal episodic memory in Persian speaker patients with MS. Materials and methods: In this cross-sectional study, 46 patients (13 males and 33 females) with definite relapsing-remitting multiple sclerosis and 46 age, gender, and educationally-matched healthy controls were selected using convenient sampling based on inclusion criteria. The patients were divided into two groups (n=23 per group) according to the Expanded Disability Status Scale (EDSS) scores; 0-4 and 4-6. The Montreal Cognitive Assessment (MoCA) test was used to screen cognitive function and the Benson Figure test was used to evaluate the non-verbal episodic memory function. Results: Compared to healthy controls, both MS groups were found to be significantly impaired in accuracy and placement of structures of visuospatial abilities (copy trial), visual memory (immediate recall), and maintaining and retrieving visuospatial sources (delayed recall) (P< 0.05). Conclusion: Acquired brain injury in MS is associated with dysfunction of nonverbal episodic memory. In other words, MS would adversely influences patient’s performance in all stages of the visuospatial test (copy, immediate, and delayed recall). Moreover, EDSS could be regarded as a predictor for individual differences in MS patients in all stages of nonverbal episodic memory.
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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 | 0.001 |
| 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) | 0.002 | 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".