Sex and gender differences in cognitive and brain reserve: Implications for Alzheimer’s disease in women
Bibliographic record
Abstract
Women represent ⅔ of the cases of Alzheimer's disease (AD). Current research has focused on differential risks to explain higher rates of AD in women. However, factors that reduce risk for AD, like cognitive/brain reserve, are less well explored. We asked: what is known about sex and gender differences in how reserve mitigates risk for AD? We conducted a narrative review of the literature, with keywords: "sex/gender differences", "cognitive/brain reserve", "Alzheimer's Disease", and the following cognitive reserve contributors: "education", "IQ", "occupation", "cognitive stimulation", "bilingualism", "socioeconomic status", "physical activity", "social support". Sixteen papers disaggregated their data by sex. Those papers observed sex and gender differences in reserve contributors. There is also evidence that greater reserve may be more beneficial in lowering AD risk in women, although more research is needed. We discuss how traditional reserve contributors are gendered and may not capture factors that support cognition in aging women.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".