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Record W2892052813 · doi:10.1002/cphy.c160008

Breath‐Hold Diving

2018· review· en· W2892052813 on OpenAlexaff
John R. Fitz‐Clarke

Bibliographic record

VenueComprehensive physiology · 2018
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBusinessComputer science

Abstract

fetched live from OpenAlex

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.013

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.

Opus teacher head0.176
GPT teacher head0.378
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations83
Published2018
Admission routes1
Has abstractyes

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