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Record W1970050048 · doi:10.1121/1.2884083

Tissue mimicking materials for dental ultrasound

2008· letter· en· W1970050048 on OpenAlexfundno aff
Rahul Singh, Martin O. Culjat, Warren S. Grundfest, E. R. Brown, Shane N. White

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typeletter
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsnot available
FundersNational Institute of Dental and Craniofacial ResearchNational Institutes of HealthMcMaster UniversityTelemedicine and Advanced Technology Research CenterU.S. Department of Defense
KeywordsMaterials scienceDentinImaging phantomUltrasoundHard tissueAttenuationBiomedical engineeringAcoustic impedanceSoft tissueEnamel paintAcousticsDentistryComposite materialOpticsMedicineRadiologyUltrasonic sensor

Abstract

fetched live from OpenAlex

While acoustic tissue mimicking materials have been explored for a variety of soft and hard biological tissues, no dental hard tissue mimicking materials have been characterized. Tooth phantoms are necessary to better understand acoustic phenomenology within the tooth environment and to accelerate the advancement of dental ultrasound imaging systems. In this study, soda lime glass and dental composite were explored as surrogates for human enamel and dentin, respectively, in terms of compressional velocity, attenuation, and acoustic impedance. The results suggest that a tooth phantom consisting of glass and composite can effectively mimic the acoustic behavior of a natural human tooth.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.404
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations16
Published2008
Admission routes1
Has abstractyes

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