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Record W4233367835 · doi:10.32920/ryerson.14647059

Ultrasound mediated study of the electrokinetic effects in biological tissues and phantoms

2021· preprint· en· W4233367835 on OpenAlexafffund
Aditya Pandya

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUltrasoundElectrokinetic phenomenaImaging phantomBiomedical engineeringMaterials scienceAmplitudeAcousticsOpticsPhysicsNanotechnologyMedicine

Abstract

fetched live from OpenAlex

Traditional ultrasound imaging monitors the backscattering properties of the object being imaged. Many hybrid imaging techniques such as photo-acoustic imaging, electro-acoustic imaging etc. have been developed to enhance the contrast in imaging. The main objective of this study was to monitor the electrically induced mechanical changes (EIMC) in ultrasound phantoms. Changes in time shifting of the signals and amplitude changes were investigated. Images were formed using a linear array ultrasound probe based on the time-delay estimates and the amplitude changes occurring in the tissue/phantom structure. EIMC in phantoms were found to depend on the applied electric field, gelling agent concentration, and salt concentration. The dependence of EIMC on the various parameters can be explained by the stiffness and fixed charge densities (FCD) of the phantoms. Knowledge gained from experimental results and its future extensions might culminate to form a method to image tissues based on their electrokinetic properties.

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 score0.312
Threshold uncertainty score0.468

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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