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Record W2600140872 · doi:10.1615/tsfp7.850

COMPUTATION OF BLOOD FLOWS ACCOUNTING FOR RED-BLOOD CELL AGGREGATION/FRAGMENTATION

2011· article· en· W2600140872 on OpenAlexaff
A. Kane, Yves Bourgault, Alexandre Iolov, Robert G. Owens, A. Fortin

Bibliographic record

VenueProceeding of Seventh International Symposium on Turbulence and Shear Flow Phenomena · 2011
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsPolytechnique MontréalUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsMechanicsViscoelasticityDeborah numberShear rateReynolds numberBlood viscosityComputationPulsatile flowViscosityMathematicsStatistical physicsPhysicsThermodynamicsFlow (mathematics)TurbulenceAlgorithm

Abstract

fetched live from OpenAlex

This article presents flows computed in non-trivial geometries while accounting for the contribution of the red cells to the Cauchy stress using the haemorheological model of Owens (2006), Owens and Fang (2006). In this model the local shear viscosity is determined in terms of both the local shear rate and the average rouleau size, with the latter being the solution of an advection-reaction equation. The model describes the viscoelastic, shear-thinning and hysteretic behaviour of flowing blood, and includes non-local effects in the determination of the blood viscosity and stresses. We present numerical results for a two dimensional aneurytic channel under both steady and pulsatile flow conditions. We compare the flows for two sets of physiologically relevant Reynolds and Deborah numbers. A 3-D flow in a section of a patientspecific carotid artery is also presented.

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)0.002
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.025
GPT teacher head0.247
Teacher spread0.222 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

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