Power Output Manipulation from Below to Above the Gas Exchange Threshold Results in Exacerbated Performance Fatigability
Bibliographic record
Abstract
INTRODUCTION: Performance fatigability is substantially greater when exercising in the severe- versus heavy-intensity domain. However, the relevance of the boundary between moderate- and heavy-intensity exercise, the gas exchange threshold (GET), to performance fatigability is unclear. This study compared alterations in neuromuscular function during work-matched exercise above and below the GET. METHODS: Seventeen male participants completed work-matched cycling for 90, 110, and 140 min at 110%, 90%, and 70% of the GET, respectively. Knee extensor isometric maximal voluntary contraction (MVC), high-frequency doublets (Db100), low- to high-frequency doublet ratio (Db10:100), and voluntary activation were measured at baseline, 25%, 50%, 75%, and 100% of task completion. During the initial baseline visit and after each constant work rate bout, ramp-incremental exercise was performed, and peak power output and oxygen uptake (V̇O 2peak ) were determined. RESULTS: After the 70% and 90% GET trials, similar reductions in MVC (-14% ± 6% and -14% ± 8%, respectively, P = 0.175) and Db100 (-7% ± 9% and -6% ± 9%, respectively, P = 0.431) were observed. However, for a given amount of work completed, reductions in MVC (-25% ± 15%, P = 0.008) and Db100 (-12% ± 8%, P = 0.029) were up to 2.6-fold greater during the 110% than the 90% GET trial. Peak power output and V̇O 2peak during ramp-incremental exercise were reduced by 7.0% ± 11.3% and 6.5% ± 9.3%, respectively, after the 110% GET trial relative to the baseline ramp ( P ≤ 0.015), with no changes after the moderate-intensity trials ( P ≥ 0.078). CONCLUSIONS: The lack of difference in fatigability between the trials at 70% and 90% GET, coupled with the greater fatigability at 110% relative to 90% GET, shows that exceeding the moderate- to heavy-intensity boundary has implications for performance fatigability, while also impairing maximal exercise performance capacity.
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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) | 0.003 | 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".