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Record W2067345775 · doi:10.1115/sbc2009-206544

Accounting for Differences Between Echo Particle Image Velocimetry (EPIV) and Pulse Wave Doppler (PWD) Velocity Measurements

2009· article· en· W2067345775 on OpenAlexaffabout
Andrew Walker, Clifton R. Johnston, Gary Dobson

Bibliographic record

VenueASME 2009 Summer Bioengineering Conference, Parts A and B · 2009
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDoppler effectParticle image velocimetryVelocimetryLaser Doppler velocimetryAcoustic Doppler velocimetryOpticsPulse (music)Echo (communications protocol)PhysicsAcousticsMaterials scienceBlood flowMechanicsTurbulenceComputer scienceMedicine

Abstract

fetched live from OpenAlex

Currently, an echo particle image velocimetry (ePIV) system for the investigation of in vivo blood flow and shear stress is under development at the University of Calgary. To date, encouraging preliminary results have been obtained when comparing ePIV derived velocities to analytical solutions. However, large discrepancies were noted between our steady state ePIV derived velocities and velocities measured using pulse wave Doppler (PWD). Ultrasound beam thickness, off axis centerline measurements and PWD angle of interrogation likely account for the differences observed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score1.000

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 head0.052
GPT teacher head0.250
Teacher spread0.199 · 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.

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

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueASME 2009 Summer Bioengineering Conference, Parts A and BSame topicUltrasound and Hyperthermia ApplicationsFrench-language works237,207