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Record W2168737490 · doi:10.1109/mwsym.1993.276789

An improved 2D-FDTD algorithm for hybrid mode analysis of quasi-planar transmission lines

2002· article· en· W2168737490 on OpenAlexaff
S. Xiao, R. Vahldieck

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFinite-difference time-domain methodLimitingElectric power transmissionPlanarAlgorithmFinite difference methodComputer scienceGridWave propagationMathematical analysisTopology (electrical circuits)MathematicsPhysicsGeometryOpticsCombinatoricsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

A significantly improved two-dimensional finite-difference time-domain (FDTD) method is proposed for the full-wave analysis of guided wave structures. By using a phase shift beta Delta z along the z-direction (propagation direction) and assuming the limiting case of Delta z, the propagation constant of hybrid modes can be calculated by using a two-dimensional mesh with a truly two-dimensional grid size. By appropriately arranging variables, only a real impulse response is involved. A novel grading scheme allowing a gradually nonequidistant mesh in three dimensions is introduced.>

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.288
Teacher spread0.272 · 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 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

Citations34
Published2002
Admission routes1
Has abstractyes

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