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Record W2594521395

Application of single source surface integral equations to transverse electric scattering by a lossy dielectric

2002· article· en· W2594521395 on OpenAlexaff
Radu Curiac, I.R. Ciric

Bibliographic record

VenueInternational Symposium on Antenna Technology and Applied Electromagnetics · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIntegral equationElectric-field integral equationScatteringDielectricPhysicsSurface (topology)Volume integralMathematical analysisComputational physicsClassical mechanicsOpticsMathematicsGeometryQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

Formulations of electromagnetic wave scattering by lossy dielectric bodies in terms of volume integral equations require a large amount of computation due to the volume distribution of unknown sources and some of them are unreliable when applied to dielectric bodies with large values of relative permittivity. The analysis of wave scattering by coupled surface integral equations reduces the dimensionality of the problem by employing unknown sources only distributed over the surface of the dielectric bodies. Two unknown surface current densities are used in these equations. Wave scattering by lossless homogeneous dielectrics has also been modeled quantitatively by using only a single unknown surface current distribution instead of the two distributions of electric and magnetic surface currents in the classical coupled surface integral equations, thus reducing by half the number of unknowns required. The integral equation satisfied by the density of this surface current is the so-called single source surface integral equation (SSSIE) [1]-[3].

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 categoriesMeta-epidemiology (narrow)
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 score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.203
Teacher spread0.198 · 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.

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

Citations0
Published2002
Admission routes1
Has abstractyes

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