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Record W2118397565 · doi:10.1109/aps.2006.1710814

Feasibility Study of Forward Electromagnetic Solutions Used in Breast Tumor Detection

2006· article· en· W2118397565 on OpenAlexaff
Yunpeng Song, Natalia K. Nikolova

Bibliographic record

Venue2006 IEEE Antennas and Propagation Society International Symposium · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSolverInterface (matter)Computer scienceInverse problemRepresentation (politics)Microwave imagingInverseCoupling (piping)Finite-difference time-domain methodMicrowaveMathematical optimizationApplied mathematicsMathematicsPhysicsMathematical analysisTelecommunicationsOpticsEngineeringMechanical engineeringGeometry

Abstract

fetched live from OpenAlex

Forward electromagnetic (EM) solutions must be sufficiently accurate in order to be used in the solution of the inverse problem of microwave medical imaging. Two well-known issues related to the adequacy of the forward EM solutions are: 1) the feasibility of 2-D approximations and 2) the effect of the skin interface. In this paper, we present a systematic study using the time-domain EM solver XFDTD to assess the applicability of related approximations. This preliminary investigation leads us to believe that a 2-D simulation is not an adequate representation of the forward problem and may be misleading when testing inverse solvers. Also, the skin interface must be modeled correctly regardless of how well the properties of the coupling medium match those of the breast tissue. Ultra-wide band responses are studied and numerous plots are presented to support our conclusions.

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)0.002
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.218
Teacher spread0.209 · 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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