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Record W4381802833 · doi:10.3390/mi14071281

Performance Analysis of an Aperture-Coupled THz Antenna for Diagnosing Breast Cancer

2023· article· en· W4381802833 on OpenAlexaff
Anupma Gupta, Vipan Kumar, Dinesh Kumar Garg, Mohammed H. Alsharif, Abu Jahid

Bibliographic record

VenueMicromachines · 2023
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTerahertz radiationAntenna (radio)Breast cancerWidebandAperture (computer memory)Microwave imagingOpticsMicrowavePhysicsAcousticsComputer scienceMedicineCancerTelecommunicationsInternal medicine

Abstract

fetched live from OpenAlex

The most important technique for exposing early-stage breast cancer is terahertz imaging. It aids in lowering the number of breast cancer-related fatalities and enhancing the quality of life. An essential component of developing the THz imaging system for high-quality photos is choosing the right sensor. In this article, a wideband antenna for microwave imaging of breast tissue with an operating frequency of 30 GHz (107 GHz to 137 GHz) is constructed and analyzed. An aperture-coupled antenna with an optimized ground aperture is proposed and analyzed, which made it possible to obtain better and consistent impedance matching in the wideband spectrum. The variation of backscattered signal energy in body tissue is assessed with healthy breast tissue and in the presence of malignant cells. A significant difference in energy scattering is observed for both situations. The suggested antenna's linear and stable time domain characteristics make it an appropriate component for THz imaging technology.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 integrity0.0010.000
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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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

Citations18
Published2023
Admission routes1
Has abstractyes

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