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Record W2592300228

Dielectric resonator antennas for application in microwave tomography

2006· article· en· W2592300228 on OpenAlexaff
Hamidreza Memarzadeh Tehran, Jean‐Jacques Laurin, Yves Goussard, Raman Kashyap

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMicrowaveResonatorDielectric resonatorDielectricFabricationMaterials scienceOpticsDielectric resonator antennaDirectional antennaMicrowave imagingSlot antennaAcousticsOptoelectronicsPhysicsAntenna (radio)Electrical engineeringEngineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This paper describes two prototype dielectric resonator antennas (DRA) designed to provide highly localized near field distributions, which are required in microwave tomography. Both antennas were designed and built for operation at an ISM frequency of 2.45 GHz. The first prototype is a dielectric cylindrical rod operating on the HE 11 guided mode and the second one is a more compact DRA consisting of a rod of rectangular cross section, partially metallized. This DRA operates on the rod's quasi-TEM mode and it has less severe fabrication tolerances. The measured near-field characteristics of both antennas are compared, and near-field images in the presence of a small scatterer simulating a tumor are presented.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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