660 EP100 – Identifying residual gaps in explosive strength with isokinetic dynamometry
Bibliographic record
Abstract
Background Optimal strength plays a pivotal role in reducing the risk of sports-related injuries; nonetheless, the unique characteristics of strength warrant specific and focused assessment. Objective to evaluate the association between peak torque and the rate of force development (RFD) in a cohort of elite level athletes Design cross-sectional study Setting data obtained from athletes training at Institut National du Sport du Québec Participants 183 healthy athletes partaking in national or international level sport competitions (73 males and 104 females) Assessment of Risk Factors evaluation of torque strength using a Con-TREX MJ system at 60°/s for knee joint muscles and 180°/s for shoulder joint muscles Main Outcome Measurements Spearman rank correlations were employed to compare average peak torque and rates of force development in knee flexion and extension for lower-body sports, as well as shoulder internal and external rotation for upper-body sports. Furthermore, potential sex differences were assessed using Student t-tests. Results Correlation analyses showed high to very high correlation between mean peak torque and RFD for the knee (rho=0.89 to 0.97) and for the shoulder (rho=0.83 to 0.99). Overall, the male athletes exhibited greater values of shoulder torque and RFD than the female athletes (p<0.01). Males were stronger in knee flexion as well, but group differences were not significant for knee extension torque (p=0.08) or RFD (p=0.29). Further analysis of the residuals indicate that outliers strayed further from the mean below the group average (IQR>1.5). Conclusions Mean peak torque and RFD were highly correlated in this cohort of athletes. However, sizeable outliers were present when below-average RFD was present for athletes with typical peak torque. Further research is necessary to explore whether these characteristics are observed in injured athletes, and whether insufficient RFD values may be a better indicator of readiness to return to sport than peak torque.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".