Is <i>V</i>O<sub>2</sub> supressed during nonapnoeic facial submersion?
Bibliographic record
Abstract
The mammalian dive response (DR) is described as oxygen-conserving based on measures of bradycardia, peripheral vasoconstriction, and decreased ventilation (V̇ E ). Using a model of simulated diving, this study examined the effect of nonapnoeic facial submersions (NAFS) on oxygen consumption (V̇O 2 ). 19 participants performed four 2-min NAFS with 8 min of rest between each. Two submersions were performed in 5 °C water, 2 in 25 °C water. Heart rate (HR) was collected using chest strap monitors. A tube connected to the inspired port of a non-rebreathing valve allowed participants to breathe during facial submersion. Expired air was directed to a metabolic cart to determine V̇O 2 and V̇ E . Baseline (BL) HR, V̇O 2 , and V̇ E values were determined by the average during the 2 min prior to facial submersion; cold shock response (CSR) values were the maximum during the first 30 s of facial submersion; and NAFS values were the minimum during the last 90 s of facial submersion. A 2-way repeated-measures ANOVA indicated that both HR and V̇ E were greater during the CSR (92.5 ± 3.6 beats/min, 16.3 ± 0.8 L/min) compared with BL (78.9 ± 3.2 beats/min, 8.7 ± 0.4 L/min), while both were decreased from BL during the NAFS (60.0 ± 4.0 beats/min, 6.0 ± 0.4 L/min) (all, p < 0.05). HR CSR was higher and HR NAFS lower in 5 °C versus 25 °C water (p < 0.05), while V̇ E was greater in 5 °C conditions (p < 0.05). V̇O 2 exceeded BL during the CSR and decreased below BL during the NAFS (BL: 5.3 ± 0.1, CSR: 9.8 ± 0.4, NAFS: 3.1 ± 0.2 mL·kg −1 ·min −1 , p < 0.05). The data illustrate that NAFS alone contributes to the oxygen conservation associated with the human DR.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".