Changes in ankle work, foot work, and tibialis anterior activation throughout a long run
Bibliographic record
Abstract
BACKGROUND: The ankle and foot together contribute to over half of the positive and negative work performed by the lower limbs during running. Yet, little is known about how foot kinetics change throughout a run. The amount of negative foot work may decrease as tibialis anterior (TA) electromyography (EMG) changes throughout longer-duration runs. Therefore, we examined ankle and foot work as well as TA EMG changes throughout a changing-speed run. METHODS: Fourteen heel-striking subjects ran on a treadmill for 58 min. We collected ground reaction forces, motion capture, and EMG. Subjects ran at 110%, 100%, and 90% of their 10-km running speed and 2.8 m/s multiple times throughout the run. Foot work was evaluated using the distal rearfoot work, which provides a net estimate of all work contributors within the foot. RESULTS: Positive foot work increased and positive ankle work decreased throughout the run at all speeds. At the 110% 10-km running speed, negative foot work decreased and TA EMG frequency shifted lower throughout the run. The increase in positive foot work may be attributed to increased foot joint work performed by intrinsic foot muscles. Changes in negative foot work and TA EMG frequency may indicate that the TA plays a role in negative foot work in the early stance of a run. CONCLUSION: This study is the first to examine how the kinetic contributions of the foot change throughout a run. Future studies should investigate how increases in foot work affect running performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".