Normative Data for the<i>Rappel libre/Rappel indicé à 16 items</i>(16-item Free and Cued Recall) in the Elderly Quebec-French Population
Bibliographic record
Abstract
Performance on verbal memory tests is generally associated with socio-demographic variables such as age, sex, and education level. Performance also varies between different cultural groups. The present study aimed to establish normative data for the Rappel libre/Rappel indicé à 16 items (16-item Free and Cued Recall; RL/RI-16), a French adaptation of the Free and Cued Selective Reminding Test (Buschke, 1984 Buschke, H. (1984). Cued recall in amnesia. Journal of Clinical Neuropsychology , 6 , 433–440.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]; Grober, Buschke, Crystal, Bang, & Dresner, 1988 Grober, E. , Buschke, H. , Crystal, H. , Bang, S. , & Dresner, R. (1988). Screening for dementia by memory testing. Neurology , 38 , 900–903.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). The sample consisted of 566 healthy French-speaking older adults (50–88 years old) from the province of Quebec, Canada. Normative data for the RL/RI-16 were derived from 80% of the total sample (normative sample) and cross-validated using the remaining participants (20%; validation sample). The effects of participants’ age, sex, and education level were assessed on different indices of memory performance. Results indicated that these variables were independently associated with performance. Normative data are presented as regression equations with standard deviations (symmetric distributions) and percentiles (asymmetric distributions).
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".