The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) Study Neuropsychology Battery of the Canadian Consortium on Neurodegeneration in Aging (CCNA): Battery Development and Description
Bibliographic record
Abstract
The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) is an observational study of more than 1100 participants across the dementia spectrum. This research note describes the development and features of the neuropsychological research battery, which is available in English and French. The training of staff and procedures for quality assurance are described. The battery assesses learning and memory, processing speed, attention, executive function, visuoperceptual processing, and language, and the available test scores are described. We outline our goals for future work including: (1) increasing the sociodemographic diversity of the participant cohorts, (2) determining the psychometric properties of the battery, (3) establishing robust normative data from control participants followed longitudinally, and (4) examining longitudinal data on individuals at risk of dementia and across the dementia spectrum. The COMPASS-ND neuropsychology data will provide a unique open-access database of deeply phenotyped participants with or at risk of dementia for Canadian and international researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".