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Record W2094099316 · doi:10.1155/2012/851234

A Prototype System for Measuring Microwave Frequency Reflections from the Breast

2012· article· en· W2094099316 on OpenAlexafffund
Jeremie Bourqui, J.M. Sill, Elise Fear

Bibliographic record

VenueInternational Journal of Biomedical Imaging · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche Médicale
KeywordsMicrowave imagingMicrowaveSensitivity (control systems)RadarComputer scienceImaging phantomBreast imagingAcousticsMedical physicsComputer visionElectronic engineeringMammographyTelecommunicationsOpticsMedicinePhysicsBreast cancerEngineering

Abstract

fetched live from OpenAlex

Microwave imaging of the breast is of interest for monitoring breast health, and approaches to active microwave imaging include tomography and radar-based methods. While the literature contains a growing body of work related to microwave breast imaging, there are only a few prototype systems that have been used to collect data from humans. In this paper, a prototype system for monostatic radar-based imaging that has been used in an initial study measuring reflections from volunteers is discussed. The performance of the system is explored by examining the mechanical positioning of sensor, as well as microwave measurement sensitivity. To gain insight into the measurement of reflected signals, simulations and measurements of a simple phantom are compared and discussed in relation to system sensitivity. Finally, a successful scan of a volunteer is described.

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)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.022
GPT teacher head0.274
Teacher spread0.251 · 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

Citations128
Published2012
Admission routes2
Has abstractyes

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