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Low-Cost Methodology for Estimation of Breast Shape using Microwave Signals

2025· article· en· W4414165107 on OpenAlexfundno aff
Daniela M. Godinho, Afonso Simões, Inês A. Correia, Bruno Mendes, Gonçalo Canastra, Joana Rajão‐Saraiva, Rodrigo Dias, Raquel C. Conceição

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaResearch Executive AgencyMinisterio de Economía y CompetitividadEuropean CommissionMcGill University
KeywordsMicrowave imagingAntenna (radio)MicrowaveSimple (philosophy)Estimation theoryEstimation

Abstract

fetched live from OpenAlex

The retrieval of the body shape can be crucial ahead of medical Microwave Imaging (MWI) reconstruction.Current state-of-the-art methods provide accurate estimations of the body shape but they require additional hardware and may be computationally intensive and time-consuming.In this paper, we propose a simple method using the original measurements of an MWI acquisition, and we assess the performance of the method under different conditions.The results show the estimation accuracy varies with the complexity of the shape under examination, antenna configuration and data source.The estimated median errors for some antenna positions were as low as 0.4 mm.An optimised estimation was obtained by fine-tuning parameters for each simulated or experimental scenario.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score0.416

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 head0.045
GPT teacher head0.307
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes1
Has abstractyes

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