Principles of Longevity and Aging: Interventions to Enhance Older Adulthood
Bibliographic record
Abstract
Healthy aging and prevention efforts for the elderly warrant attention in a world where the average mortality rate continues to increase. The current literature review is an overview of current findings related to healthy aging and recommendations for older adults who are living longer and healthier; as well as facing the physical and psychological challenges that come with extended life. Staying active, eating right, utilizing social and environmental resources, employing coping skills developed across the lifespan, as well as developing new strategies can enhance the quality of life for older adults. Helping professionals from all disciplines who are able to recognize the needs of this growing group, and recognize the resiliency factors inherent in healthy aging, have the best chance of designing and implementing successful preventionand intervention efforts.The purpose of the present literature review is twofold: 1) To systematically review the important factors that affect an individual’s longevity and to raise awareness of the importance of those factors that are within one’s control; and 2) To inform health care providers of prevention efforts important to older adults;encouraging an integration of research and practice to preventative efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".