Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Breath-hold diving is practiced by recreational divers, seafood divers, military divers, and competitive athletes. It involves highly integrated physiology and extreme responses. This article reviews human breath-hold diving physiology beginning with an historical overview followed by a summary of foundational research and a survey of some contemporary issues. Immersion and cardiovascular adjustments promote a blood shift into the heart and chest vasculature. Autonomic responses include diving bradycardia, peripheral vasoconstriction, and splenic contraction, which help conserve oxygen. Competitive divers use a technique of lung hyperinflation that raises initial volume and airway pressure to facilitate longer apnea times and greater depths. Gas compression at depth leads to sequential alveolar collapse. Airway pressure decreases with depth and becomes negative relative to ambient due to limited chest compliance at low lung volumes, raising the risk of pulmonary injury called "squeeze," characterized by postdive coughing, wheezing, and hemoptysis. Hypoxia and hypercapnia influence the terminal breakpoint beyond which voluntary apnea cannot be sustained. Ascent blackout due to hypoxia is a danger during long breath-holds, and has become common amongst high-level competitors who can suppress their urge to breathe. Decompression sickness due to nitrogen accumulation causing bubble formation can occur after multiple repetitive dives, or after single deep dives during depth record attempts. Humans experience responses similar to those seen in diving mammals, but to a lesser degree. The deepest sled-assisted breath-hold dive was to 214 m. Factors that might determine ultimate human depth capabilities are discussed. © 2018 American Physiological Society. Compr Physiol 8:585-630, 2018.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 it