Is Everything a Challenge for Multiple Sclerosis patients? Nonverbal Semantic Memory Performance in Iranian Relapsing-Remitting Multiple Sclerosis Patients
Bibliographic record
Abstract
Objectives: The objective of the current study was to evaluate the nonverbal semantic memory performance of MS patients and compare it with their healthy counterparts. Materials and methods: In this study, 70 patients with definite relapsing-remitting multiple sclerosis(15 men and 55 women) and 70 healthy individuals of comparable demographics (age, gender, and education) from patients’ relatives and family members were selected based on convenient sampling. The patients recruited for this study were divided into two groups based on their Montreal Cognitive Assessment (MoCA) scores. The first group of patients (MS1) with MoCA scores of 18-25, and the MoCA scores of the second group (MS2) ranged from 10 -17. All of the participants were right-handed, originally born in Mashhad, Iran, and native speakers of Persian. To assess the nonverbal semantic memory performance of the participants, the picture version of The Camel and Cactus Test (CCT) was selected and administered from the Cambridge Semantic Memory battery test. Results: The results revealed that there was no significant difference between the MS1 and the Healthy Controls group in living and man-made variables, while MS 2 performed significantly different compared to other groups in these variables. The results also showed that all three groups of participants performed significantly different from each other in reaction time variable. Conclusion: The findings showed that cognitive impairment in multiple sclerosis patients did not affect their nonverbal semantic memory performance, however, it had an impact on their reaction time. Bangladesh Journal of Medical Science Vol.20(2) 2021 p.390-395
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".