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Record W1976648155 · doi:10.1109/ultsym.2013.0532

Simultaneous assessment of bone thickness and velocity for ultrasonic computed tomography using transmission-echo method

2013· article· en· W1976648155 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransducerUltrasonic sensorEcho (communications protocol)Materials scienceRobustness (evolution)AcousticsTransmission (telecommunications)Cortical boneBiomedical engineeringPhysicsComputer scienceChemistryEngineeringTelecommunicationsAnatomy

Abstract

fetched live from OpenAlex

The robustness and accuracy of the transmission-echo (TE) method is investigated on simultaneous thickness and velocity estimation of double-layered thin bone samples. Twenty-two pairs of bovine cortical samples were assembled and measured by two pairs of immersion transducers with nominal frequencies of 1MHz and 2.25MHz. For each measurement, the TOF of six pulses contained by one transmission and two echo signals were detected and then used for the calculation. The mean relative errors of effective samples for 1MHz and 2.25MHz transducers are 4.87% and 7.13% on cortical thickness estimation, and 4.65% and 5.88% on velocity assessment, respectively. For both thickness and velocity measurement, the experiments in low frequency provide more accurate estimations, and the velocity measurement shows more stability. It is demonstrated that the TE method has the potential to simultaneously estimate the cortical thickness and ultrasonic wave velocity for the mimic model of long bones.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.622
Threshold uncertainty score0.449

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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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

Quick stats

Citations8
Published2013
Admission routes1
Has abstractyes

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