Effect of race distance on performance fatigability in male trail and ultra‐trail runners
Bibliographic record
Abstract
The etiology of changes in lower-limb neuromuscular function, especially to the central nervous system, may be affected by exercise duration. Direct evidence is lacking as few studies have directly compared different race distances. This study aimed to investigate the etiology of deficits in neuromuscular function following short versus long trail-running races. Thirty-two male trail runners completed one of five trail-running races as LONG (>100 km) or SHORT (<60 km). Pre- and post-race, maximal voluntary contraction (MVC) torque and evoked responses to electrical nerve stimulation during MVCs and at rest were used to assess voluntary activation and muscle contractile properties of knee-extensor (KE) and plantar-flexor (PF) muscles. Transcranial magnetic stimulation (TMS) was used to assess evoked responses and corticospinal excitability in maximal and submaximal KE contractions. Race distance correlated with KE MVC (ρ = -0.556) and twitch (ρ = -0.521) torque decreases (p ≤ .003). KE twitch torque decreased more in LONG (-28 ± 14%) than SHORT (-14 ± 10%, p = .005); however, KE MVC time × distance interaction was not significant (p = .073). No differences between LONG and SHORT for PF MVC or twitch torque were observed. Maximal voluntary activation decreased similarly in LONG and SHORT in both muscle groups (p ≥ .637). TMS-elicited silent period decreased in LONG (p = .021) but not SHORT (p = .912). Greater muscle contractile property impairment in longer races, not central perturbations, contributed to the correlation between KE MVC loss and race distance. Conversely, PF fatigability was unaffected by race distance.
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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".