A comparison of the performances between healthy older adults and persons with Alzheimer's disease on the Rey auditory verbal learning test and the Test de rappel libre/rappel indicé 16 items
Bibliographic record
Abstract
The aim of this research was to compare the performances of healthy elderly (n=40) and individuals with Alzheimer's disease (AD, n=40) on the RL/RI 16, a French adaptation of the Free and cued selective reminding test (FCSRT) and on the Rey auditory verbal learning test (RAVLT). These two verbal episodic memory tests are frequently used in clinical practice in French-speaking populations. Results showed that the RAVLT demonstrated a slightly better sensitivity and sensibility than the RL/RI 16. The RAVLT allowed to classify participants of the two groups without any overlap. Moreover, no floor effect was observed in the RAVLT in AD and ceiling effects were less pronounced in normal controls that in the RL/RI 16. Results observed in the RL/RI 16 showed important ceiling effects and a decline in performance on free recall throughout trials in AD patients. Nonetheless, the latter tool was less sensitive to recency effects than the RAVLT and may thus provide a more realistic view of the long-term memory performance of these patients. The semantic cues provided in the RL/RI 16 appeared to increase intrusions in AD whereas the interference list in the RAVLT was the first source of false recognitions in both healthy elderly and AD. In conclusion, this paper demonstrates both the advantages and disadvantages of these two tools in the evaluation of episodic memory in elderly with and without cognitive deficits.
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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 | 0.002 |
| 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 | 0.001 | 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".