Modeling of Mechanisms Providing the Overall Control of Human Circulation
Bibliographic record
Abstract
Multiple humoral and nervous mechanisms, each influencing the cardiovascular system (CVS) with its specific dynamics and power, had been evolutionarily saved both in animals and in human organisms. Most of such mechanisms are considered to be controllers of CVS’s function, but there is no concept clearly explaining the interaction of global and local controllers in intact human organisms under physiological or pathological conditions. Methodological and ethical constraints create practically insuperable obstacles while experiments on animals mainly concern artificial situations with certain switched-of mechanisms. Currently, mathematical modeling and computer simulations provide the most promising way for expanding and deepening our understanding of regulators’ interactions. As most of CVS’s models describe only partial control mechanisms, a special model (SM) capable of simulating every combination of control mechanisms is encouraged. This paper has three goals: i) to argue the uncial modeling concept and its physiological basis, ii) to describe SM, and iii) to give basic information about SM’s test research. SM describes human hemodynamics, which is under influence of arterial baroreceptor reflexes, peripheral chemoreceptor reflexes, central (CRAS) and local (lRAS) renin-angiotensin systems, local ischemia, and autoregulation of total brain flow. SM, performed in form of special software (SS), is tested under specific endogenous and/or exogenous alterations. The physiologist using SS can easily construct the desirable configuration of regulator mechanisms, their actual state, and scenarios of computer experiments. Tests illustrated the adequateness of SM, are the first step of SM’s research. Nuances of the interaction of modeled regulator mechanisms have to be illustrated in special publications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".