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Record W2171188457 · doi:10.1109/22.883862

Microwave detection of breast cancer

2000· article· en· W2171188457 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.

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2000
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMicrowave imagingMammographyMicrowaveBreast cancerComputer scienceSignal processingElectronic engineeringCancerTelecommunicationsEngineeringMedicineRadar

Abstract

fetched live from OpenAlex

Breast cancer affects many women, and early detection aids in fast and effective treatment. Mammography, which is currently the most popular method of breast screening, has some limitations, and microwave imaging offers an attractive alternative. A microwave system for breast tumor detection that uses previously introduced confocal microwave imaging techniques is presented in this paper. The breast is illuminated with an ultrawide-band pulse and a synthetic scan of the focal point is used to detect tumors; however, the geometric configuration and algorithms are different from those previously used. The feasibility of using small antennas for tumor detection is investigated. Signal processing algorithms developed to mitigate the dominant reflection from the skin are described, and the effectiveness of these skin subtraction algorithms is demonstrated. Images of homogeneous and heterogeneous breast models are reconstructed with various numbers of antennas. Both the influence of antenna spacing and the suitability of simplified models for system evaluation are examined.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.824

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 head0.005
GPT teacher head0.210
Teacher spread0.206 · 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