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Record W3197653125 · doi:10.1152/ajpheart.00422.2021

Blood pressure oscillations impact signal-averaged sympathetic transduction of blood pressure: implications for the association with resting sympathetic outflow

2021· article· en· W3197653125 on OpenAlexafffund
Massimo Nardone, Carlin Katerberg, Anthony V. Incognito, André L. Teixeira, Lauro C. Vianna, Philip J. Millar

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsToronto General HospitalUniversity of Guelph
FundersCanadian Institutes of Health ResearchOntario Ministry of Economic Development, Job Creation and TradeNatural Sciences and Engineering Research Council of CanadaAmerican Physiological SocietyMinistério da Ciência, Tecnologia e InovaçãoConselho Nacional de Desenvolvimento Científico e TecnológicoCanada Foundation for InnovationGovernment of CanadaGovernment of Ontario
KeywordsBlood pressureCardiologyOutflowInternal medicineSympathetic nervous systemSIGNAL (programming language)MedicineSympathetic activityAssociation (psychology)Heart ratePhysicsPsychologyComputer science

Abstract

fetched live from OpenAlex

The current signal-averaging technique for calculating sympathetic transduction of blood pressure does not consider the arterial pressure at which each muscle sympathetic burst occurs. A burst firing when mean arterial pressure is above the operating pressure was associated with a decrease in blood pressure. Thus, individuals with higher muscle sympathetic nerve activity demonstrate a reduced sympathetic transduction owing to the weighted contribution of more sympathetic bursts at higher levels of arterial pressure.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.252
Teacher spread0.240 · 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 designObservational
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

Citations16
Published2021
Admission routes2
Has abstractyes

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