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Models of cerebrovascular reactivity in BOLD-fMRI and transcranial Doppler ultrasound

2025· article· en· W4411302508 on OpenAlexfundno aff
Genevieve Hayes, Sierra Sparks, Daniel P. Bulte, Joana Pinto

Bibliographic record

VenueJournal of Applied Physiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchEngineering and Physical Sciences Research CouncilUniversity of OxfordRhodes ScholarshipsClarendon FundUK Research and Innovation
KeywordsTranscranial DopplerMedicinePsychologyTranscranial magnetic stimulationNeuroscienceCardiology

Abstract

fetched live from OpenAlex

This study compares cerebrovascular reactivity (CVR) between transcranial Doppler ultrasound (TCD) and BOLD-fMRI using a hypercapnia protocol. Linear intermodality correlations across [Formula: see text] ranges validate linear CVR modeling. Significant variability in a four-parameter sigmoid model was mitigated by fixing span and bound parameters, supporting a two-parameter model for improved agreement but reducing sensitivity to diminished reserve. These findings clarify which CVR metrics are consistent between TCD and BOLD-fMRI, advancing multimodal integration for cerebrovascular health assessment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.007
GPT teacher head0.233
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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Same venueJournal of Applied Physiology→Same topicCerebrovascular and Carotid Artery Diseases→French-language works237,207→