Bibliographic record
Abstract
When right atrial pressure (Pra) is greater than zero (atmospheric pressure), cardiac output is determined by the intersection of two functions, cardiac function and return function, which is used here to mean the determinants of venous return. When Pra < or = 0, flow is only determined by circuit function. The objective of this analysis was to determine the potential changes in return function that need to occur to allow the maximum cardiac output during exercise when Pra < or = 0 or is constant. The analysis expands on the model of Green and Jackman and includes the effects of changes in circuit parameters, including venous resistance, changes in capacitance, and muscle contractions. The analysis is based on the model of the circulation proposed by Permutt and co-workers, which assumes that the systemic circulation has two lumped compliant regions in parallel with independent inflow and outflow resistances. Changes in total flow in this model can come about by changes in the distribution of flow between the regions, recruitment of unstressed vascular volume, and changes in the regional venous resistances. The data for the analysis are from previous animal studies and are normalized to a 70-kg man. The major conclusions are that, to achieve the high cardiac output that occurs at peak exercise, there need to be marked changes in the distribution of blood flow, recruitment of unstressed volume, and the venous resistance draining vascular beds. A consequence of the increase in peripheral flow is a marked increase in pressure in the veins of the working muscle. Muscle contractions are potentially a very important mechanism for transiently decreasing this pressure and preventing excessive filtration of plasma during exercise.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".