Decompression sickness in breath-hold divers: A review
Bibliographic record
Abstract
Although it has been generally assumed that the risk of decompression sickness is virtually zero during a single breath-hold dive in humans, repeated dives may result in a cumulative increase in the tissue and blood nitrogen tension. Many species of marine mammals perform extensive foraging bouts with deep and long dives interspersed by a short surface interval, and some human divers regularly perform repeated dives to 30-40 m or a single dive to more than 200 m, all of which may result in nitrogen concentrations that elicit symptoms of decompression sickness. Neurological problems have been reported in humans after single or repeated dives and recent necropsy reports in stranded marine mammals were suggestive of decompression sickness-like symptoms. Modelling attempts have suggested that marine mammals may live permanently with elevated nitrogen concentrations and may be at risk when altering their dive behaviour. In humans, non-pathogenic bubbles have been recorded and symptoms of decompression sickness have been reported after repeated dives to modest depths. The mechanisms implicated in these accidents indicate that repeated breath-hold dives with short surface intervals are factors that predispose to decompression sickness. During deep diving, the effect of pulmonary shunts and/or lung collapse may play a major role in reducing the incidence of decompression sickness in humans and marine mammals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".