Performance Fatigability at Task Failure and Beyond: Distinct Patterns of Recovery Following Constant Load Versus Intermittent Cycling Exercise
Bibliographic record
Abstract
The total work completed during an exercise session is often assumed to be the primary factor influencing the kinetics of post-exercise recovery. However, the duration of work and rest periods during high intensity interval training (HIIT) have been shown to impact the magnitude of physiological stress and could also impact post-exercise recovery. The aim of this study was to characterize the recovery time course of neuromuscular function following work-to-rest matched HIIT protocols with different work interval durations and conducted to task failure. Participants (n=12, n=6 females) completed a ramp incremental exercise test to determine peak power output (PPO). In a randomized order, participants completed 3 cycling protocols at 90% PPO: (i) 3 min work, 3 min passive rest HIIT (HIIT3min), (ii) 1 min work, 1 min passive rest HIIT (HIIT1min), and (iii) constant load (CL) cycling. Femoral nerve electrical stimuli during maximal voluntary contractions (MVC) of isometric knee extension were performed at baseline, task failure (TF), and TF+1min, TF+4min, and TF+8min to delineate the time course of neuromuscular function recovery. MVC force declined to the same level following the three conditions at TF and demonstrated a partial recovery within TF+8min (time effect: P<0.001). The evoked muscle twitch force declined more following the CL compared to HIIT1min at TF (P = 0.013) and showed a faster recovery within TF+8min (P<0.024). Voluntary activation decreased at TF in the HIIT1min but not in HIIT3min or CL (interaction effect: P<0.023) and fully recovered within TF+8min. Central and peripheral components of neuromuscular function demonstrate distinct time courses of recovery between CL exercise and work:rest matched HIIT protocols with different work interval durations.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".