State space modeling of cardiovascular regulation
Bibliographic record
Abstract
A linear state-space model (LSSM) of cardiovascular regulation was developed using measurements of instantaneous lung volume (ILV), heart rate (HR) and arterial blood pressure (APE) in 6 normal human volunteers (male, age: 22-30 yr., median 24 yr). The system order and an orthogonal basis for the state space of the system were estimated using the singular value decomposition (SVD) of a data matrix. The LSSM parameters were then found from the solution of an over-determined set of equations in least squares. The LSSM improves the phase function estimate and shows that (1) HR and ABP is most responsive to slow changes in ILV tidal volume when mean breathing frequency is 0.2-0.4 Hz (p>0.95) although system gain at these frequencies is reduced. (2) ANS responsiveness to changes in tidal volume increases linearly with frequency at slow (0.05-0.1 Hz) breathing rates (p>0.95). It is concluded that paced breathing system identification is a fast and non-invasive way to accurately characterize some of the physiological links between respiration, blood pressure and heart rate variability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".