Short-term cold-water immersion does not alter neuromuscular fatigue development during high-intensity intermittent exercise
Bibliographic record
Abstract
Aims: Pre-exercise cold-water immersion affects physical performance under ambient environment, however the mechanisms leading to this decrease remains to be elucidated. The purpose was to determine whether short-term lower-body immersion in cold water could induce acute changes in the development of neuromuscular fatigue after high-intensity exercise. Methods: Ten participants performed on two separate visits a fatigue task (60 intermittent isometric maximal voluntary contractions maintained over 3 s and spaced by 2 s of recovery) once after lower-body cold-water immersion (Pre-Cooling, 6 min at 8.9°C ± 1.6°C) and another time without prior immersion (Control). Before and after the fatigue task, neuromuscular function was assessed during voluntary or evoked contractions (electrical stimulation performed on the femoral nerve) on contracted and relaxed on knee extensor muscles. Results: No differences in neuromuscular fatigue were measured between Pre-Cooling and Control conditions, despite maximal voluntary contraction reductions (−49 and −48%, respectively, both p < 0.05), peripheral contractile capacities (both -28%, p < 0.05). Additionally, rate of perceived exhaustion increases over time for both conditions (both p < 0.05) with differences in the time course. Discussion: Lower body immersion in extreme cold water for a short period of time was not a sufficient stimulus to induce a significant disruption of human body homeostasis: neuromuscular function was not significantly altered during a maximum intensity fatigue task.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".