Biomechanical determinants of running economy
Bibliographic record
Abstract
Running economy (RE) defined as the submaximal rate of oxygen consumption during running, has been correlated with better performance. Biomechanical factors such as spatiotemporal parameters and lower extremity mechanics play a significant role in influencing RE. However, the relationship between RE and biomechanical variables in middle-distance running shoes is still unclear. In this study, twenty-one healthy male runners (age: 32.5 ± 5.6 years, height: 1.70 ± 0.10 m, body mass: 69.9 ± 7.3 kg) performed running trials on the treadmill. Physiological and biomechanical variables, including joint angles, moments, angular velocities, powers, ground reaction forces, and spatiotemporal parameters were analyzed. Multiple linear regression and backward stepwise regression analyses were employed to identify key biomechanical determinants of RE. The final regression model identified that the hip positive power, knee extension angular velocity, ankle plantarflexion angular velocity and negative power, and metatarsophalangeal extension angular velocity explained 73% of RE variability. Therefore, focus on optimizing these biomechanical variables, possible with specific shoe properties, could lead to enhanced RE in middle-distance running shoes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".