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Record W2033906980 · doi:10.1109/sice.2006.315708

Autonomic Nervous Activity Revealed by a New Physiological Index /spl rho//sub max/ Based on Cross-Correlation between Mayer-Wave Components of Blood Pressure and Heart Rate

2006· article· en· W2033906980 on OpenAlexaff
Akira Tanaka, Norihiro Sugita, Makoto Yoshizawa, Yasuyuki Shiraishi, Tomoyuki Yambe, Shin‐ichi Nitta

Bibliographic record

Venue2006 SICE-ICASE International Joint Conference · 2006
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsHeart rateAutonomic nervous systemIndex (typography)Heart rate variabilityBlood pressureCorrelation coefficientCorrelationArtificial intelligenceMathematicsComputer scienceMedicineStatisticsInternal medicineWorld Wide Web

Abstract

fetched live from OpenAlex

The authors have proposed a new physiological index ρmaxwhich is the maximum cross-correlation coefficient between blood pressure and heart rate whose frequency components are limited to the Mayer wave-band (0.04-0.15 Hz). The advantages of this index are small individual difference and high reproducibility compared with other physiological indices which are calculated independently single cardiovascular measurements. The previous study showed that the index ρmaxis possible to assess visually-induced motion sickness. However, the relation between the proposed index and autonomic nervous activity has not been clarified yet. In this study, the change in ρmaxduring sympathetic or parasympathetic blockage has been investigated in comparison with conventional indices in an animal experiment. The results have indicated that ρmaxdoes not have information on parasympathetic nerve activity but sympathetic one

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.276
Teacher spread0.238 · 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

Citations7
Published2006
Admission routes1
Has abstractyes

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