Size Matters: Spleen and Lung Volumes Predict Performance in Human Apneic Divers
Bibliographic record
Abstract
Humans share with seals the ability to contract the spleen and increase circulating hematocrit, which may improve apneic performance by enhancing gas storage. Seals have large spleens and while human spleen size is small in comparison, it shows great individual variation. Unlike many marine mammals, human divers rely to a great extent on lung oxygen stores, but the impact of lung volume on competitive apnea performance has never been determined. We studied if spleen- and lung size correlated with performance in elite apnea divers. Volunteers were 14 male apnea world championship participants, with a mean (SE) of 5.8 (1.2) years of previous apnea training. Spleen volume was calculated from spleen length, width, and thickness measured via ultrasound during rest, and vital capacity via spirometry. Accumulated competition scores from dives of maximal depth, time, and distance were compared to anthropometric measurements and training data. Mean (SE) diving performance was 75 (4) m for constant weight depth, 5 min 53 (39) s for static apnea and 139 (13) m for dynamic apnea distance. Subjects' mean height was 184 (2) cm, weight 82 (3) kg, vital capacity (VC) 7.3 (0.3) L and spleen volume 336 (32) mL. Spleen volume did not correlate with subject height or weight, but was positively correlated with competition score (r = 0.57; P < 0.05). Total competition score was also positively correlated with VC (r = 0.54; P < 0.05). The three highest scoring divers had the greatest spleen volumes, averaging 538 (53) mL, while the three lowest-scoring divers had a volume of 270 (71) mL (P < 0.01). VC was also greater in the high-scorers, at 7.9 (0.36) L as compared to 6.7 (0.19) L in the low scorers (P < 0.01). Spleen volume was reduced to half after 2 min of apnea in the highest scoring divers, and the estimated resting apnea time gain from the difference between high and low scorers was 15 s for spleen volume and 60 s for VC. We conclude that both spleen- and lung volume predict apnea performance in elite divers.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".