Does altitude level of a prior time‐trial modify subsequent exercise performance in hypoxia and associated neuromuscular responses?
Bibliographic record
Abstract
Abstract We examined the influence of prior time‐trials performed at different altitudes on subsequent exercise in moderate hypoxia and associated cardiometabolic and neuromuscular responses. In normobaric hypoxia (simulated altitude 2000 m; FiO2: 0.163), 10 healthy males performed (1) an incremental test to exhaustion (VO2max_2000) and (2) a test to exhaustion at 80% of the power output associated to VO2max_2000 for a reference time (947 ± 336 sec). Thereafter, two sessions were conducted in a randomized order: a cycle time‐trial corresponding to the reference time (TT1) followed 22 min later (passive rest at 2000 m) by a 6‐min cycle time‐trial (TT2). TT1 was either performed at 2000 or 3500 m (FiO2: 0.135), while TT2 was always performed at 2000 m. As expected, during TT1, the mean power output (247 ± 42 vs. 227 ± 37 W; P < 0.001) was higher at 2000 than 3500 m. During TT2, the mean power output (256 ± 42 vs. 252 ± 36 W) did not differ between conditions. Before and after TT1, maximal isometric voluntary contraction torque in knee extensors (pooled conditions: −7.9 ± 8.4%; P < 0.01), voluntary activation (−4.1 ± 3.1%; P < 0.05), and indices of muscle contractility (peak twitch torque: −39.1 ± 11.9%; doublet torques at 100 Hz: −15.4 ± 8.9%; 10/100 Hz ratio: −25.8 ± 7.7%; all P < 0.001) were equally reduced at 2000 m or 3500 m. Irrespective of the altitude of TT1, neuromuscular function remained similarly depressed after TT1 both before and after TT2 at 2000 m. A prior time‐trial performed at different altitude influenced to the same extent performance and associated cardiometabolic and neuromuscular responses during a subsequent exercise in moderate hypoxia.
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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".