Measuring Cerebrovascular Reactivity: The Dynamic Response to a Step Hypercapnic Stimulus
Bibliographic record
Abstract
We define cerebral vascular reactivity (CVR) as the ratio of the change in blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) signal (S) to an increase in blood partial pressure of CO2 (PCO2): % Δ S/Δ PCO2 mm Hg. Our aim was to further characterize CVR into dynamic and static components and then study 46 healthy subjects collated into a reference atlas and 20 patients with unilateral carotid artery stenosis. We applied an abrupt boxcar change in PCO2 and monitored S. We convolved the PCO2 with a set of first-order exponential functions whose time constant τ was increased in 2-second intervals between 2 and 100 seconds. The τ corresponding to the best fit between S and the convolved PCO2 was used to score the speed of response. Additionally, the slope of the regression between S and the convolved PCO2 represents the steady-state CVR (ssCVR). We found that both prolongations of τ and reductions in ssCVR (compared with the reference atlas) were associated with the reductions in CVR on the side of the lesion. τ and ssCVR are respectively the dynamic and static components of measured CVR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".