The Assessment of Isometric, Dynamic, and Sports-Specific Upper-Body Strength in Male and Female Competitive Surfers
Bibliographic record
Abstract
The primary purpose of this study was to investigate gender differences in the dynamic strength index (DSI): an assessment of upper-body dynamic strength relative to maximal isometric strength. The secondary purpose was to investigate gender differences in the dynamic skill deficit (DSD): an assessment of sports-specific dynamic strength relative to maximal isometric strength, and its association with a sports-specific performance measure in surfers. Nine male (age = 30.3 ± 7.3 yrs) and eight female (age = 25.5 ± 5.2 yrs) surfers undertook three upper-body assessments: isometric push-up, dynamic push-up, and a force plate pop-up to determine the DSI and DSD. The performance measure of time taken to pop-up (TTP) was recorded. No gender differences for the DSI (d = 0.48, p = 0.33) or DSD (d = 0.69, p = 0.32) were observed. Normalized peak force (PF) of the isometric push-up, dynamic push-up, and force plate pop-up were significantly greater in males (p ≤ 0.05), with males recording significantly quicker TTP (d = 1.35, p < 0.05). The results suggest that male and female surfers apply a similar proportion of their maximal strength in sports-specific movements. However, greater normalized isometric and dynamic strength in males resulted in greater sports-specific PF application and a faster TTP. It would appear favorable that female surfers improve their maximal strength to facilitate sports-specific pop-up performance.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".