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Record W2985550810 · doi:10.1029/2018rs006783

Electromagnetic Scattering in Curvilinear Coordinates Using a Generalized Functions Method

2019· article· en· W2985550810 on OpenAlexafffund
Murilo T. Silva, Eric W. Gill, Weimin Huang

Bibliographic record

VenueRadio Science · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsCurvilinear coordinatesCoordinate systemSpherical coordinate systemMathematical analysisElectromagnetic fieldCylindrical coordinate systemBoundary value problemScatteringEllipsoidal coordinatesMaxwell's equationsMathematicsElliptic coordinate systemParabolic coordinatesPhysicsField (mathematics)System of linear equationsGeometryOpticsLog-polar coordinatesQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract A system of equations for calculating the electric field in curvilinear coordinates without imposing external boundary conditions is proposed. First, the system of equations is derived using generalized functions, without imposing external boundary conditions or a coordinate system. Then, in order to demonstrate the use of the system of equations, the derived system is applied to the case of a spherical scatterer, which is then narrowed to the case of a perfect electrically conducting (PEC) sphere. It is shown that for the particular case of a PEC sphere, the resulting field expression agrees with the Stratton‐Chu solution for the Maxwell's equations, confirming that the proposed method can be used to reach a general solution for the electromagnetic field scattered by a PEC sphere, which allows for the calculation of its cross section.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.275
Teacher spread0.266 · 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 designTheoretical or conceptual
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

Citations6
Published2019
Admission routes2
Has abstractyes

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