Dynamic Changes of Performance Fatigability and Muscular O2 Saturation in a 4-km Cycling Time Trial
Bibliographic record
Abstract
PURPOSE: The current study characterized the performance fatigability etiology, immediately after exercise cessation, and its relation to the dynamic changes in muscle O2 saturation (SmO2) at different TT phases. METHODS: Twelve males performed three separated TT of different distances, in a crossover counterbalanced design, until the end of the fast-start (FS, 827 ± 135 m), even-pace (EP, 3590 ± 66 m), or end-spurt (ES, 4000 m) TT phases. Performance fatigability was characterized by using isometric maximal voluntary contractions (IMVC), whereas the maximal voluntary activation (VA) and contractile function of knee extensors (e.g., peak torque of potentiated twitches [TwPt]) were evaluated using electrically evoked contractions performed before and immediately after each exercise bouts. SmO2, power output (PO), and EMG were also recorded. RESULTS: Immediately after the FS phase, there were lower values for IMVC (-23%), VA (-8%), and TwPt (-43%) (all P < 0.001), but no further changes were measured after EP (IMVC, -28%; VA, -8%; TwPt, -38%). After the ES phase, IMVC (-34%) and TwPt (-59%) further decreased compared with the previous phases (P < 0.05). There were lower SmO2 and higher EMG/PO values during FS and ES compared with EP phase. CONCLUSION: FS and EP phases had similar performance fatigability etiology, but ES showed further impairments in contractile function. This later finding might be due to the abrupt changes in SmO2 and EMG/PO because of the high exercise intensity during the ES, which elicited maximal decline in contractile function at the finish line.
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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".