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Record W2085767824 · doi:10.1088/0031-9155/54/13/004

The influence of the boundary conditions on longitudinal wave propagation in a viscoelastic medium

2009· article· en· W2085767824 on OpenAlexaff
Hani Eskandari, Ali Baghani, Septimiu E. Salcudean, Robert Rohling

Bibliographic record

VenuePhysics in Medicine and Biology · 2009
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsViscoelasticityLongitudinal waveAcousticsWave propagationMechanicsCompressibilityDisplacement (psychology)Particle displacementBoundary (topology)PhysicsBoundary value problemBoundary element methodFinite element methodOpticsMathematical analysisMathematicsAmplitude

Abstract

fetched live from OpenAlex

In this paper, the effect of the boundary conditions and excitation dimensions on the speed of longitudinal waves in a medium is investigated. It is shown that with appropriate boundary conditions, a low-speed longitudinal wave can be generated in the medium which can be tracked by standard pulse-echo ultrasound motion tracking techniques. Three different cases of boundary conditions are explored in which the longitudinal wave speed in an incompressible material can be as high as the acoustic wave speed or as low as the shear wave speed. It is shown that the displacement spectrum can be used to estimate the wave speed in a viscoelastic medium. Numerical simulations with 3D viscoelastic finite element models and experiments on tissue-mimicking phantoms are performed to validate the theory.

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)0.001
metaresearch head score (Gemma)0.015
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.349
Teacher spread0.285 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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