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Recent Advances in the Theory and Applications of the Surface-Volume-Surface Electric Field Integral Equation

2018· article· en· W2894107135 on OpenAlexaff
Zhuotong Chen, Reza Gholami, Jamiu Mojolagbe, Shucheng Zheng, Vladimir Okhmatovski

Bibliographic record

Venue2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsElectric-field integral equationIntegral equationVolume integralSurface integralSurface (topology)Electric fieldField (mathematics)Gaussian surfacePhysicsElectromagnetic fieldScatteringComputational electromagneticsVolume (thermodynamics)Summation equationLine integralMathematical analysisClassical mechanicsMathematicsGeometryOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

In the past several years [1] we have been developing a new class of single-source integral equation (SSIE) for scattering problems on non-magnetic dielectric objects. The new SSIE is formed through constraining of a single source surface integral representation of the electromagnetic fields with volume electric field integral equation (V-EFIE). Unlike previously known SSIEs which feature only field translations from the surface of the scatterer back to it's surface, the new integral equation features fields translations from the surface of the scatterer to its volume and from the volume of the scatterer to its surface. Due to such fields translations the new SSIE is called the Volume-Surface-Volume Electric Field Integral Equation (SVS-EFIE).

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)0.003
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: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.007
GPT teacher head0.243
Teacher spread0.237 · 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
GenreReview

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
Published2018
Admission routes1
Has abstractyes

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