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Record W2566729639 · doi:10.2495/dne-v12-n1-30-43

Flow patterns in helical-type graft: Biomedical applications

2016· article· en· W2566729639 on OpenAlexvenueno aff
Elena Bernad, S. I. Bernad, A. F. Totorean, Alin Bosioc, I. Sargan

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsFlow (mathematics)Type (biology)Materials scienceMechanicsBiomedical engineeringEngineering drawingComputer scienceEngineeringPhysicsBiology

Abstract

fetched live from OpenAlex

The long-term success of arterial bypass surgery is often limited by the progression of intimal hyperplasia at the anastomosis between the graft and the native artery.The experimental models were manufactured from glass tubing with a constant internal diameter of 8 mm, fashioned into a straight configuration and helical configuration.The aim of this study was to determine the three-dimensional flow structures in the proximal anastomosis under pulsatile flow conditions and to establish the significant differences between the straight and helical graft.In the anastomosis domain, a stable region of recirculation is observed near the occluded end of the artery, which forces the flow to move into the perfused host coronary artery.A comparison between experimentally measured velocity patterns in straight and helical grafts confirms the robust nature of the secondary flows in the helical geometry.The helical configuration promotes the mixing effect of vortex motion such that the particles are mixed into the blood stream in the junction area.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.008
GPT teacher head0.268
Teacher spread0.260 · 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
Published2016
Admission routes1
Has abstractyes

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