Does cognitive aging follow an orchid and dandelion phenomenon?
Bibliographic record
Abstract
Cognitive reserve reflects the brain’s intrinsic adaptive capacity against the neurodegenerative effects of aging. The maintenance or enhancement of the brain’s cognitive reserve plays a crucial role in mitigating the severity of pathologies associated with aging. A new movement, social prescribing, which focuses on prescribing lifestyle activities as a treatment for patients, is growing in popularity as a solution against aging pathologies. However, few studies have demonstrated a clear impact of lifestyle activities on individual cognitive health, outside of floor and ceiling effects. Understanding who benefits from which lifestyle factors remains unclear. Here, we investigated the potential effects of lifestyle activities on individuals’ cognitive health from more than 3,530 older adults using a stratification method and advanced analysis technique. Our stratification methods allowed us to observe a new result: older adults who had relatively average cognitive scores were not impacted by lifestyle factors. By comparison, older adults with very high or very low cognitive scores were highly impacted by lifestyle factors. These findings expand the orchid and dandelion theory to the aging field, regarding the biological sensitivity of individuals to harmful and protective environmental effects. Our discoveries demonstrate the role of individual differences in the aging process and its importance for social prescribing programs.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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".