Pulmonary capillary recruitment and distention in mammalian lungs: species similarities
Bibliographic record
Abstract
Pulmonary arterial pressure rises minimally during exercise. The pulmonary microcirculation accommodates increasing blood flowviarecruitment of pulmonary capillaries and, at higher flows, by distention of already perfused capillaries. The flow transition range between recruitment and distention has not been studied or compared across mammalian species, including humans. We hypothesised that the range would be similar. Functional pulmonary capillary surface area (FCSA) can be estimated using validated metabolic techniques. We reviewed data from previous studies in three mammalian species (perfused rabbit lungs and dog lung lobes, and exercising humans) and generated blood flow–FCSA curves over a range of flows. We noted where the curves diverged from the theoretical line of pure recruitment (Recruitment) and determined the flow where the curve slope equalled 50% that of Recruitment, or equalled that of a theoretical curve representing full capillary distention (Distention). The three mammalian species have similar flow ranges for the transition from predominantly recruitment to predominantly distention, with dogs having the highest transition point. Within the physiological range of most daily activity, the species are similar and accommodate increasing blood flow mainlyviarecruitment, with progressive distention at higher flows. This is highly relevant to pulmonary physiology during exercise.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".