Impacts of creatine on the health of elderly individuals: a bibliometric study
Bibliographic record
Abstract
The need to seek greater health and quality of life gave rise to the search for supplements, mainly creatine, which helps maintain the health of elderly people. This research aimed to produce a bibliometric analysis of scientific production on the impacts of creatine supplementation on the health and quality of life of elderly people, aiming to identify knowledge gaps in this area. This is a bibliometric study with exploratory and descriptive specificity carried out using the Web of Science and Scopus databases. Comprehensive data was obtained such as the exponential growth scenario of articles produced between the years 2021 and 2022. The magazines that publish the most on the subject were: "Nutrients" and “The Journal of Strength and Conditioning Research”. It is noteworthy that the United States is the country that leads scientific production on this topic, followed by Canada, where McMaster University is located, which stands out as the institution with the largest number of publications. It was found that creatine has an effective role in combating muscle atrophy and sarcopenia related to aging, when associated with physical activity, helping to improve quality of life. Furthermore, the scarcity of scientific works addressing this subject in detail is highlighted. It is necessary for new studies to be carried out on this topic.
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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 | 0.009 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.130 | 0.214 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".