Bibliographic record
Abstract
As the global population is projected to age substantially in coming decades, the number of individuals who will develop Alzheimer disease (AD) is expected to rise dramatically. We have come to understand that AD is likely to be multidetermined through interactions between heritable causal and susceptibility genes, environmental exposures, midlife health status, and lifestyle choices. In addition, mounting evidence suggests that the neuropathological processes characteristic of AD can be detected several years before the onset of clinical symptoms. Thus, AD is now considered to have presymptomatic, prodromal (mild cognitive impairment), and dementia phases. Through cerebrospinal fluid biomarkers, volumetric neuroimaging, functional neuroimaging, and cognitive stress tests, individuals at significant risk for developing dementia can now be identified with greater sensitivity and specificity. Consequently, there is growing attention to identify interventions to halt or delay the onset of AD. The biological capacities of neurogenesis and neuroplasticity and the related concepts of brain and cognitive reserve provide a rationale for developing techniques to maintain or enhance the cognitive abilities of older persons to sufficiently prevent dementia. This has led to the emergence of a new "brain fitness" commercial industry in which "products" are being marketed and sold to consumers to "keep your brain sharp." However, most available brain fitness products have scant scientific evidence to support their effectiveness. Nevertheless, ongoing research advances do support the potential for memory and other intellectual functions to be strengthened and maintained through cognitive training, physical exercise, dietary choices, social engagement, and psychological stress reduction.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.234 | 0.112 |
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".