Lack of Evidence for Crossover Fatigue with Plantar Flexor Muscles
Bibliographic record
Abstract
The occurrence and mechanisms underlying non-local or crossover muscle fatigue is an ongoing issue. This study aimed to investigate crossover fatigue of the plantar flexor muscles. Sixteen recreationally active males (n = 6) and females (n = 10) visited the laboratory for four sessions and performed a single 5-s pre-test maximal voluntary isometric contraction (MVIC) with each plantar flexors muscle. Thereafter, the fatigue intervention involved two 100-s MVICs (60-s recovery) with their dominant plantar flexors or rested for 260-s (control). Subsequently, in two separate sessions, Hoffman reflexes (H-reflex) were evoked in the non-dominant, non-exercised, leg before and following the dominant leg fatigue or control intervention (Fatigue-Reflex and Control-Reflex conditions). MVIC forces and volitional (V)-waves were monitored in the non-dominant leg in the other two sessions (Fatigue-MVIC and Control-MVIC) before and after the intervention (fatigue or control) as well as during 12 repeated MVICs and immediately thereafter. Despite the force reduction in the dominant leg (42.4%, p = 0.002), no crossover force deficit with single (F(1,9) = 0.02, p = 0.88, pƞ2 = 0.003) or repeated (F(1,9) = 0.006, p = 0.93, pƞ2 = 0.001) MVIC testing were observed. The H-reflex did not change after the fatigue (F(1,7) = 0.51; p = 0.49; pƞ2 = 0.06) or repeated MVICs (F(1,8) = 0.27; p = 0.61; pƞ2 = 0.03). There were also no crossover effects of fatigue on the V-wave with single (F(1,8) = 3.71, p = 0.09, pƞ2 = 0.31) or repeated MVICs (F(1,6) = 1.45, p = 0.27, pƞ2 = 0.19). Crossover fatigue was not evident with the plantar flexors nor any significant changes in H-reflex and V-waves in the soleus muscle. This finding suggests that crossover fatigue may not necessarily occur in slow-twitch predominant muscle groups.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".