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Record W1994268840 · doi:10.1115/sbc2008-191770

Influence of Inlet Secondary Curvature on Image-Based CFD Models of the Carotid Bifurcation

2008· article· en· W1994268840 on OpenAlexaff
Sang-wook Lee, David A. Steinman

Bibliographic record

VenueASME 2008 Summer Bioengineering Conference, Parts A and B · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBifurcationInletMechanicsComputational fluid dynamicsCurvatureWork (physics)Flow (mathematics)Common carotid arteryCarotid bifurcationImage (mathematics)Process (computing)Carotid arteriesPhysicsComputer scienceMathematicsEngineeringGeometryMechanical engineeringThermodynamicsComputer visionCardiologyNonlinear systemMedicine

Abstract

fetched live from OpenAlex

In image-based CFD modelling of carotid bifurcation hemodynamics, it is often not possible (or at least not convenient) to impose measured velocity profiles at the common carotid artery (CCA) inlet. Instead, fully-developed velocity profiles are usually imposed based on measured flow rates. Previous work from our group showed that this is reasonable [1], in the sense that errors made in doing so are substantially less than uncertainties inherent in the model construction process itself. In that study, long helical inlet sections were imposed to induce asymmetric (Dean-type) velocity flows profiles consistent with in vivo velocity profiles measured by others at the CCA [2, 3].

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)0.000
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 score0.434
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.021
GPT teacher head0.244
Teacher spread0.223 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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Same venueASME 2008 Summer Bioengineering Conference, Parts A and BSame topicCardiovascular Health and Disease PreventionFrench-language works237,207