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Record W2105704179 · doi:10.1109/tap.2010.2048844

Balanced Antipodal Vivaldi Antenna With Dielectric Director for Near-Field Microwave Imaging

2010· article· en· W2105704179 on OpenAlexaff
Jeremie Bourqui, M. Okoniewski, Elise Fear

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVivaldi antennaAntipodal pointAntenna (radio)DirectivityOpticsAntenna apertureMicrowave imagingMicrowaveDielectricAperture (computer memory)Dipole antennaAntenna measurementPhysicsMaterials scienceComputer scienceTelecommunicationsAcousticsOptoelectronicsMathematics

Abstract

fetched live from OpenAlex

A balanced antipodal Vivaldi antenna is designed to be used as a sensor for a microwave breast cancer detection system. The antenna has the ability to send short electromagnetic pulses into the near-field, with low distortion, low loss and in a directional manner. The antenna directivity is further improved by the inclusion of a novel feature in the antenna aperture called a “director” which consists of a profiled piece of higher dielectric constant material. Several simulated results are successfully confirmed with measurements. Reflections of a tumor placed in a breast model are simulated for two cases, namely a balanced antipodal Vivaldi antenna with and without a director. Greater tumor responses are recorded with the director present, demonstrating the potential of this feature for microwave breast imaging.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.201
Teacher spread0.196 · 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

Citations386
Published2010
Admission routes1
Has abstractyes

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