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Record W2075737532 · doi:10.1115/sbc2009-204323

Image-Based CFD Modelling of Hemodynamic Factors in Aneurysm Formation Using a Novel Approach for Digital Removal of Saccular Aneurysms

2009· article· en· W2075737532 on OpenAlexaff
Matthew D. Ford, Yiemeng Hoi, Marina Piccinelli, Luca Antiga, David A. Steinman

Bibliographic record

VenueASME 2009 Summer Bioengineering Conference, Parts A and B · 2009
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsHemodynamicsAneurysmSaccular aneurysmPathogenesisRadiologyComputer scienceMedicineBiomedical engineeringCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Although local hemodynamic forces are widely believed to play a role in aneurysm pathogenesis, the hemodynamic mechanisms have not been confirmed in a prospective manner. Ideally, one would identify the patient-specific vessel that is prone to aneurysm formation and follow it longitudinally to investigate the associated aneurysm formation factors or mechanisms. However, such studies are not practical in humans, and so the knowledge to predict aneurysm formation at a specific location, a priori, is not available.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.887

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 head0.054
GPT teacher head0.266
Teacher spread0.212 · 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 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
Published2009
Admission routes1
Has abstractyes

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Same venueASME 2009 Summer Bioengineering Conference, Parts A and BSame topicAortic aneurysm repair treatmentsFrench-language works237,207