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Record W2994468562

BIOMEDICAL ULTRASOUND IMAGING FROM 1 TO 1000 MHZ

2009· article· en· W2994468562 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian acoustics · 2009
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsUltrasoundTransducerUltrasonic sensorAcousticsMaterials scienceImage resolutionBandwidth (computing)Instrumentation (computer programming)Acoustic microscopyRangingOpticsBiomedical engineeringMicroscopyComputer sciencePhysicsEngineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Many of the developments in the field of ultrasound imaging are focused on technological improvements to improve the signal to noise of the instrumentation or in the use of new techniques to increase the soft tissue contrast. Contrast in an ultrasound image is based on the strength of backscattered ultrasound. Increase in the transducer bandwidth increases the ultrasound spatial resolution, leading to higher frequencies being used to image smaller structures to provide better axial and lateral resolution. The use of acoustic microscopy has helped in reproducing scattering patterns using smaller diameter beads at frequencies between 100 and 1,000 MHz. Investigations have been conducted using instrumentation that allows ultrasonic interrogation with frequencies ranging between 1-1000 MHz.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.983

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 head0.006
GPT teacher head0.235
Teacher spread0.229 · 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