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Record W2104599282 · doi:10.1109/ultsym.1998.765306

Experimental verification of ensemble model for scattering by microbubbles population in a contrast agent

2002· article· en· W2104599282 on OpenAlexaff
Chien Ting Chin, Peter N. Burns

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrobubblesScatteringBubbleContrast (vision)TransducerAcousticsPopulationHarmonicOpticsAmplitudeBroadbandSecond-harmonic imaging microscopyPhysicsMaterials scienceUltrasoundMechanicsSecond-harmonic generation

Abstract

fetched live from OpenAlex

A theoretical contrast agent model, extending existing single bubble models to a population of simulated bubbles, was previously reported to produce time-domain scattered signals which compared well qualitatively to experiments. Here, experiments were carried out to test this model quantitatively. DPM-115 (Dupont-Merck Inc) flowing in a chamber was exposed to 5 MHz pulsed ultrasound with various bandwidths. Scattered signals were detected at 90/spl deg/ by a broadband receive transducer. The experimental results generally confirm the authors' model for predicting scattered signals, but the measured second harmonic scattering is 10 dB lower than the theoretical prediction. It was also observed that scattering is increased at high transmitted amplitude (>1.5 MPa). The disruptible shell is believed to be a possible cause for both effects, and it is suggested that the shell is very important in understanding the acoustic response of the contrast agent.

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)0.002
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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