Pulmonary Gas Exchange and Acid‐Base Balance During Exercise
Bibliographic record
Abstract
As the first step in the oxygen-transport chain, the lung has a critical task: optimizing the exchange of respiratory gases to maintain delivery of oxygen and the elimination of carbon dioxide. In healthy subjects, gas exchange, as evaluated by the alveolar-to-arterial PO2 difference (A-aDO2), worsens with incremental exercise, and typically reaches an A-aDO2 of approximately 25 mmHg at peak exercise. While there is great individual variability, A-aDO2 is generally largest at peak exercise in subjects with the highest peak oxygen consumption. Inert gas data has shown that the increase in A-aDO2 is explained by decreased ventilation-perfusion matching, and the development of a diffusion limitation for oxygen. Gas exchange data does not indicate the presence of right-to-left intrapulmonary shunt developing with exercise, despite recent data suggesting that large-diameter arteriovenous shunt vessels may be recruited with exercise. At the same time, multisystem mechanisms regulate systemic acid-base balance in integrative processes that involve gas exchange between tissues and the environment and simultaneous net changes in the concentrations of strong and weak ions within, and transfer between, extracellular and intracellular fluids. The physicochemical approach to acid-base balance is used to understand the contributions from independent acid-base variables to measured acid-base disturbances within contracting skeletal muscle, erythrocytes and noncontracting tissues. In muscle, the magnitude of the disturbance is proportional to the concentrations of dissociated weak acids, the rate at which acid equivalents (strong acid) accumulate and the rate at which strong base cations are added to or removed from muscle.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".