Application of a multicompartment dynamical model to multimodal optical imaging for investigating individual cerebrovascular properties
Bibliographic record
Abstract
Biophysical models of hemodynamics provide a tool for quantitative multimodal brain imaging by allowing a deeper understanding of the interplay between neural activity and blood oxygenation, volume and flow responses to stimuli. Multicompartment dynamical models that describe the dynamics and interactions of the vascular and metabolic components of evoked hemodynamic responses have been developed in the literature. In this work, multimodal data using near-infrared spectroscopy (NIRS) and diffuse correlation flowmetry (DCF) is used to estimate total baseline hemoglobin concentration (HBT0) in 7 adult subjects. A validation of the model estimate and investigation of the partial volume effect is done by comparing with time-resolved spectroscopy (TRS) measures of absolute HBT0. Simultaneous NIRS and DCF measurements during hypercapnia are then performed, but are found to be hardly reproducible. The results raise questions about the feasibility of an all-optical model-based estimation of individual vascular properties.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".