The Canadian multi-ethnic research on aging (CAMERA) study: Study design, participant characteristics, and preliminary findings
Bibliographic record
Abstract
Abstract INTRODUCTION South Asian and Chinese individuals are the largest and fastest-growing ethnoracial groups in Canada, yet they remain underrepresented in dementia research. To address this gap, we established the CA nadian M ulti- E thnic R esearch on A ging (CAMERA) study. METHODS CAMERA is a longitudinal observational study conducted in Toronto, Canada, enrolling 300 adults aged 55–85 who self-identify as South Asian, Chinese, or non-Hispanic White (NHW). Participants complete in-person visits at baseline, Year 3, and Year 5, which include clinical and cognitive assessments, brain MRI, and blood biomarkers. Annual remote questionnaires track health and lifestyle. RESULTS Among 200 participants, vascular and metabolic profiles differed across groups. South Asian and Chinese participants reported greater cognitive concerns than NHW participants and had lower MoCA scores, driven primarily by language-heavy and culturally dependent items. Eye-tracking measures did not differ across groups. DISCUSSION CAMERA provides a deep phenotyping framework to investigate dementia risk and resilience in Asian Canadians.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".