CCCDTD5: Reducing the risk of later‐life dementia. Evidence informing the Fifth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD‐5)
Bibliographic record
Abstract
The Fifth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD-5) was a year-long process to synthesize the best available evidence on several topics. Our group undertook evaluation of risk reduction, in eight domains: nutrition; physical activity; hearing; sleep; cognitive training and stimulation; social engagement and education; frailty; and medications. Here we describe the rationale for the undertaking and summarize the background evidence-this is also tabulated in the Appendix. We further comment specifically on the relationship between age and dementia, and offer some suggestions for how reducing the risk of dementia in the seventh decade and beyond might be considered if we are to improve prospects for prevention in the near term. We draw to attention that a well-specified model of success in dementia prevention need not equate to the elimination of cognitive impairment in late life.
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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 | 0.027 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".