Adaptation of the Rey Auditory Verbal Learning Test and Logical Memory Subtest from the Wechsler Memory Scales – 3rd Edition to assess accelerated long‐term forgetting in adults with epilepsy
Bibliographic record
Abstract
OBJECTIVE: The present study provides normative data for adapted versions of the Rey Auditory Verbal Learning Test (RAVLT) and the Logical Memory subtest from the Wechsler Memory Scales - 3rd edition (WMS-III-LM), involving both recall and recognition procedures after a 2-week delay to assess accelerated long-term forgetting (ALF). The study also aims to achieve a clinical validation of these tests in a group of people with epilepsy (PWE). METHODS: A total of 124 (18-55 years old) healthy participants and 30 PWE undergoing presurgical monitoring for drug-resistant seizures completed these tasks. Associations between memory performance and sociodemographic, neuropsychological function, and testing factors were examined among healthy participants. Memory performance was compared between healthy and PWE groups, with special attention to forgetting rates over 2 weeks as a measure of long-term consolidation. RESULTS: Contrarily to raw recall and recognition performance, forgetting rates over 2 weeks were not significantly modulated by age or sex. As expected, higher forgetting rates and a greater prevalence of ALF were found among PWE compared with healthy participants on both tests. SIGNIFICANCE: This study offers useful normative data to assess ALF in PWE and provides clinical evidence that our adapted tests can identify long-term consolidation impairments in this population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".