SCOPUS-BASED BIBLIOMETRIC ANALYSIS OF PUBLICATION ACTIVITY IN THE FIELD OF HEALTHY AGING IN 2013-2022
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Life expectancy is getting longer, and the proportion of the elderly population is increasing. Therefore, the concept of healthy aging gains importance and attracts attention in the scientific community. This article presented a ten-year bibliometric analysis of articles on healthy aging in the Scopus database. Methods: The Scopus database was used for the bibliometric analysis. The publication list was created using the keywords «aging well» and «healthy aging.» The number of articles, active countries-journals, frequent keywords, prolific authors, and funding sources were defined. Results: An upward trend was observed in the number of articles related to healthy aging between 2013 and 2022. The five leading countries in publication activity were the United States, China, the United Kingdom, Germany, and Canada, respectively. The most prolific authors were Ferrucci, L., Franceschi, C., Evans, M.K., Bennett, D.A., and Deary, I.J. The five most active journals were Plos One, Scientific Reports, International Journal of Molecular Sciences, International Journal of Environmental Research and Public Health, and Frontiers in Aging Neuroscience. Conclusion: Bibliometric analysis is a valuable method for assessing global trends in producing scientific literature on particular topics. This study revealed an upward trend in articles on healthy aging over time, indicating an increasing interest and focus on this topic. As the elderly population grows, it is anticipated that interest in healthy aging will progressively increase. It will be advantageous for researchers interested in this field to establish collaborations with prominent authors and institutions. Thus, they will canalize their future investigation in the proper direction.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.051 | 0.182 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it