The legacy of the 2013 G8 Dementia Summit: successes, challenges, and potential ways forward
Bibliographic record
Abstract
Dementia is a public health and socioeconomic concern that is widely predicted to worsen as the proportion of older adults making up our global population increases.1 By 2050, 152 million people worldwide are expected to experience dementia, along with its associated impact. In an ambitious act to galvanise a global response, the 2013 G8 Dementia Summit was convened with a primary aim to identify a cure or disease-modifying therapy for dementia by 2025.2 New evidence has since deepened our understanding of the potential for disease-modifying therapies, making this target even more unrealistic.
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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 | 0.072 | 0.100 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.007 | 0.021 |
| Research integrity | 0.018 | 0.025 |
| Insufficient payload (model declined to judge) | 0.035 | 0.023 |
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".