Identification of cardiovascular baroreflex for probing homeostatic stability
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a method to identify the cardiovascular baroreflex parameters that are useful for probing homeostatic stability. The work is built upon a physiology-based model of the closed-loop cardiovascular and baroreflex feedback system describing the regulation of heart rate and blood pressure. Parametric sensitivity analysis is conducted on the model to classify the model parameters into high-sensitivity, low-sensitivity, and invariant groups based on their relative impacts on the system outputs. The baroreflex identification is formulated as a nonlinear optimization problem in which only high-sensitivity model parameters are identified whereas low-sensitivity and invariant parameters are fixed at their typical values. The advantage of the method is its computational efficiency without significant compromise in performance and accuracy. The method was applied to the experimental data of 10 individuals in the MIMIC Database in the PhysioBank. The promising results suggest potential of the proposed method in probing homeostasis based on the estimates of sympathetic and parasympathetic tones.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it