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Record W2154438118 · doi:10.1109/tuffc.2006.1621498

Sol-gel transition in agar-gelatin mixtures studied with transient elastography

2006· article· en· W2154438118 on OpenAlexaff
Jean‐Luc Gennisson, Guy Cloutier

Bibliographic record

VenueIEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · 2006
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsViscoelasticityMaterials scienceGelatinElasticity (physics)RheologyElastographyTransient elastographyShear (geology)AttenuationShear wavesShear modulusAcousticsBiomedical engineeringComposite materialUltrasoundChemistryOpticsPhysics

Abstract

fetched live from OpenAlex

Using the shear wave propagation in solids, the transient elastography technique has been developed to assess the elastic properties of soft tissues. Here, a new approach of transient elastography allows assessing the viscoelastic properties of soft tissues. In this paper, the method is used to follow-up the sol-gel transition of an agar-gelatin mixture noninvasively. The shear wave velocity and shear wave attenuation through the mixture were continuously monitored in the audible range of frequencies (from 50 Hz to 200 Hz). The observed changes in velocities and attenuations as a function of frequency confirmed the validity of the Voigt's model to describe the gel at its stable mechanical state. By a simple inverse problem approach, based on the one-dimensional (1-D) Helmholtz equation, the elasticity and the viscosity of such a mixture were recovered as a function of time. The results obtained are in good agreement with the literature and theoretical predictions. Overall, they demonstrate the high sensitivity of the transient elastography measurements to the rheological parameter changes in agar-gelatin mixtures during gelation.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.646
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.205
Teacher spread0.200 · 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 designBench or experimental
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

Citations40
Published2006
Admission routes1
Has abstractyes

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