The Physique of Elite Female Artistic Gymnasts: A Systematic Review
Bibliographic record
Abstract
It has been suggested that successful young gymnasts are a highly select group in terms of the physique. This review summarizes the available literature on elite female gymnasts' anthropometric characteristics, somatotype, body composition and biological maturation. The main aims were to identify: (i) a common physique and (ii) the differences, if any, among competitive/performance levels. A systematic search was conducted online using five different databases. Of 407 putative papers, 17 fulfilled all criteria and were included in the review. Most studies identified similar physiques based on: physical traits (small size and low body mass), a body type (predominance of ecto-mesomorphy), body composition (low fat mass), and maturity status (late skeletal maturity as well as late age-at-menarche). However, there was no consensus as to whether these features predicted competitive performance, or even differentiated between gymnasts within distinctive competitive levels. In conclusion, gymnasts, as a group, have unique pronounced characteristics. These characteristics are likely due to selection for naturally-occurring inherited traits. However, data available for world class competitions were mostly outdated and sample sizes were small. Thus, it was difficult to make any conclusions about whether physiques differed between particular competitive levels.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".