Human face‐only immersion in cold water reduces maximal apnoeic times and stimulates ventilation
Bibliographic record
Abstract
In two studies, the cold shock and diving responses were investigated after human face immersion without prior hyperventilation to explore the mechanism(s) accounting for reductions in maximal apnoeic times (ATmax) at low water temperatures. In study 1, ATmax, heart rate (HR) and cutaneous blood cell velocity were measured in 13 non-apnoea-trained males during apnoeic face immersion in 0, 10, 20 and 33 degrees C water and room air (AIR). In study 2, six males were measured during non-apnoeic face immersion in 0, 10 and 33 degrees C water for ventilation (VE), respiratory exchange ratio (RER), HR and oxygen consumption (VO2), as well for end-tidal partial pressures of oxygen (PET,O2) and carbon dioxide (PET,CO2). Results indicated that the ATmax of 30.7 s (S.D. 7.1 s) at 0 degrees C (P < 0.001) and 48.2 s (S.D. 16.0 s) at 10 degrees C (P < 0.05) were significantly shorter than that of 58 s in AIR or 33 degrees C. During apnoea at 0, 10, 20 and 33 degrees C, both the deceleration of HR (P < 0.05) and peripheral vasoconstriction (P < 0.05), as well as the peak HR at 0 degrees C (P = 0.002) were significantly greater than in AIR. At 0 degrees C in comparison with 33 degrees C, non-apnoeic face immersions gave peaks in (P = 0.039), RER (P = 0.025), (P = 0.032) and HR (P = 0.011), as well as lower minimum values for (P = 0.033) and HR (P = 0.002). With as the covariate, ANCOVA showed that remained significantly greater (P = 0.003) at lower water temperatures. In conclusion, during face immersion at 10 degrees C and below, there is a non-metabolic, neurally mediated cold shock-like response that shortens apnoea, stimulates ventilation and predominates over the oxygen conserving effects of the dive response.
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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".