Effects of Foot-Strike Pattern on Neuromuscular Function During a Prolonged Graded Run
Bibliographic record
Abstract
PURPOSE: To study whether, during typical-level running, non-rear-foot strikers (non-RFS) or rear-foot strikers (RFS) presented a similar or different extent of neuromuscular fatigue after a prolonged graded run. METHODS: Sixteen experienced male trail runners (8 non-RFS and 8 RFS) performed a 2.5-hour treadmill graded running exercise. Before and after exercise, neuromuscular tests were performed to assess neuromuscular fatigue of the plantar flexors. Biomechanical gait parameters were acquired with an instrumented treadmill, and electromyographic activity of the lower-limb muscles was collected as an index of muscle activation. RESULTS: There were no significant time × foot strike interactions for neuromuscular (all P ≥ .742), muscle activation (all P ≥ .157), or biomechanical (all P ≥ .096) variables. CONCLUSIONS: A dominant level running foot-strike pattern did not directly affect the extent of neuromuscular fatigue during a prolonged graded run. This suggests that no ideal running foot-strike pattern exists to minimize neuromuscular fatigue during prolonged-duration races wherein cumulative uphill and downhill segments are high, such as in trail running.
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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 | 0.000 | 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) | 0.001 | 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".