Repeated short cold-water immersions are sufficient to habituate to the cold, but do not lead to adaptations during exercise in normobaric hypoxia
Bibliographic record
Abstract
We sought to assess the effects of repeated cold-water immersions (CWI) on respiratory, metabolic, and sympathoadrenal responses to graded exercise in hypoxia. Sixteen (2 female) participants (age: 21.2 ± 1.3 years; body fat: 12.3 ± 7.7%; body surface area 1.87 ± 0.16 m2, VO2peak: 48.7 ± 7.9 mL/kg/min) underwent 6 CWI in 12.0 ± 1.2 °C. Each CWI was 5 min, twice daily, separated by ≥4 h, for three consecutive days, during which metabolic data were collected. The day before and after the repeated CWI intervention, participants ran in normobaric hypoxia (FIO2 = 0.135) for 4 min at 25%, 40%, 60%, and 75% of their sea level peak oxygen consumption (VO2peak). CWI had no effect on VO2 ( p > 0.05), but reduced the VE (CWI #1: 27.1 ± 17.8 versus CWI #6: 19.9 ± 12.1 L/min) ( p < 0.01), VT (CWI #1: 1.3 ± 0.4 vs CWI #6: 1.1 ± 0.4 L) ( p < 0.01), and VE:VO2 (CWI #1: 53.5 ± 24.1 vs CWI #6: 41.6 ± 20.5) ( p < 0.01) during subsequent CWI. Further, post exercise plasma epinephrine was lower after CWI compared to before (103.3 ± 43.1; 73.4 ± 34.6 pg/mL) ( p = 0.03), with no change in pre-exercising values (75.4 ± 30.7; 72.5 ± 25.9 pg/mL). While these changes were noteworthy, it is important to acknowledge there were no changes in pulmonary ( VE, VT, and VE:VO2) or metabolic (VO2, SmO2, and SpO2) variables across multiple hypoxic exercise workloads following repeated CWI. CWI habituated participants to cold water, but this did not lead to adaptations during exercise in normobaric 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) | 0.001 | 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 | 0.001 |
| 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".