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Record W3045533511 · doi:10.1080/09205071.2020.1791258

Sub-structure characteristic mode computation utilising field-based MM/GTD hybrid methods

2020· article· en· W3045533511 on OpenAlexaff
Anas Alakhras, D.A. McNamara

Bibliographic record

VenueJournal of Electromagnetic Waves and Applications · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputationScope (computer science)Mode (computer interface)RealisationDiffractionObject (grammar)Field (mathematics)Method of moments (probability theory)Computer scienceUniform theory of diffractionAlgorithmOpticsMathematicsPhysicsPure mathematicsArtificial intelligenceQuantum mechanics

Abstract

fetched live from OpenAlex

It is pointed out how the (sub-structure) characteristic modes of a perfect electrically conducting (PEC) object, in the presence of an electrically very large second PEC object, can be computed using a field-based hybrid method that combines the method of moments (MM) and the geometrical theory of diffraction (GTD). An example is provided to demonstrate this. This possibility has not yet been explicitly stated elsewhere (and so perhaps not realised), nor example computations provided. We believe this realisation might widen the scope of application of characteristic mode analysis.

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 categoriesnone
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 score0.372
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.286
Teacher spread0.277 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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