Indication of BOLD-Specific Venous Flow-Volume Changes from Precisely Controlled Hyperoxic vs. Hypercapnic Calibration
Bibliographic record
Abstract
Deriving cerebral metabolic rate of oxygen consumption (CMRO(2)) from blood oxygenation level-dependent (BOLD) signals involves a flow-volume parameter (α), reflecting total cerebral blood volume changes, and a calibration constant (M). Traditionally, the former is assumed a fixed value and the latter is measured under alterations in fixed inspired fractional concentrations of carbon dioxide. We recently reported on reductions in M-variability via precise control of end-tidal pressures of both hypercapnic (HC) and hyperoxic (HO) gases. In light of these findings, our aim was to apply the improved calibration alternatives to neuronal activation, making use of their distinct vasoactive natures to evaluate the α-value. Nine healthy volunteers were imaged at 3 T while simultaneously measuring BOLD and arterial spin-labeling signals during controlled, graded, HC, and HO, followed by visual (VC) and sensorimotor cortices (SMC) activation. On the basis of low M- and CMRO(2)-variability, the comparison of these calibration alternatives accurately highlighted a reduced venous flow-volume relationship (α=0.16±0.02, with α(VC)=0.12±0.04, and α(SMC)=0.20±0.02), as appropriate for BOLD modeling.
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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 | 0.000 | 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) | 0.001 | 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".