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Record W1948614838

Mode scanning for ultrasound phased arrays with six planes of symmetry

2005· article· en· W1948614838 on OpenAlexvenueno aff
Duo Chen, Robert J. McGough

Bibliographic record

VenueCanadian acoustics · 2005
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsnot available
Fundersnot available
KeywordsEquilateral trianglePlanarSymmetry (geometry)Phased arrayPlanar arrayOpticsAcousticsFinite element methodPhysicsGeometryMathematicsComputer scienceTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Modes are symmetric focal patterns that exploit the symmetry of ultrasound phased arrays and cancel the complex pressure field in multiple planes that contain the central axis. The mode scanning approach, which was originally derived for symmetric planar arrays populated with rectangular elements, is extended to include triangular and hexagonal elements. This focusing method is very useful for generating heating patterns in hyperthermia. An example of mode scanning with 6-fold symmetry shown for a flat, two-dimensional ultrasound phased array populated with equilateral triangles. The pressure field of a single triangular element is computed with the fast nearfield method, which generates pressure fields with relatively small errors. The derivation of the element driving signals that produce different model focal patterns for any mode combines the characteristic of geometric symmetry with the method of gain maximization.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0050.001

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 head0.210
Teacher spread0.202 · 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 designBench or experimental
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
Published2005
Admission routes1
Has abstractyes

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