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Record W2094877471 · doi:10.5551/jat.13.163

The Analysis and Diagnosis of Unstable Behavior of the Blood Vessel Wall with an Aneurysm Based on Noise Science

2006· article· en· W2094877471 on OpenAlexaff
A. Toshimitsu Yokobori, Michiaki Owa, Masataka Ichiki, Tomoki Satoh, Yuji Ohtomo, Yusuke Satoh, Seiichi Ohgoshi, Yoshihiko Kinoshita, Shinichi Karino

Bibliographic record

VenueJournal of Atherosclerosis and Thrombosis · 2006
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsPulsatile flowAneurysmBlood flowBlood vesselArterial wallDoppler effectSupersonic speedAccelerationCardiologyMedicineBiomedical engineeringInternal medicineRadiologyMechanicsPhysics

Abstract

fetched live from OpenAlex

Previously, one of the authors developed a noninvasive measurement method of acceleration and deceleration during the expansion process of the blood vessel wall under pulsatile pressure flow by measuring the strain rate of the blood vessel wall using a supersonic Doppler effect sensor aided by computer analysis (DPC method). In this paper, on the basis of the analysis of chaos theory, that is, the complexity of science, the unstable behavior of the blood vessel wall with an aneurysm was investigated by identifying the characteristic DPC wave forms induced by the onset and progression of aneurysm. These results showed that unstable dynamic behavior of the blood vessel wall occurs due to the progression of the aneurysm. Furthermore, using the theoretical analysis of chaos, this unstable behavior of the blood vessel wall was quantified and the fundamental principle of a noninvasive diagnostic method of the progressive degree of aneurysm was proposed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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 teacher head, 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

Citations11
Published2006
Admission routes1
Has abstractyes

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