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Record W2119519674 · doi:10.1109/tmtt.2012.2205937

Analytical Adjoint Sensitivity Formula for the Scattering Parameters of Metallic Structures

2012· article· en· W2119519674 on OpenAlexaff
M. Sadegh Dadash, Natalia K. Nikolova, J.W. Bandler

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsMcMaster University
Fundersnot available
KeywordsJacobian matrix and determinantFinite element methodSensitivity (control systems)ComputationMaxwell's equationsMatrix (chemical analysis)Applied mathematicsField (mathematics)MathematicsMethod of moments (probability theory)Mathematical analysisScatteringScattering parametersAlgorithmPhysicsElectronic engineeringPure mathematicsEngineeringQuantum mechanicsOptics

Abstract

fetched live from OpenAlex

A novel sensitivity-analysis method is proposed to compute the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> -parameter Jacobian with respect to metallic shape parameters. The formulation is analytical and is derived from Maxwell's equations directly. It is independent of the field solution method and the respective system matrix. It requires only the field solution on the object surface. The computation is a post-process and its overhead is negligible in comparison with a full-wave simulation. The method provides exact sensitivities. It is validated by the sensitivity analysis of microwave structures where the field solution is provided by commercial solvers based on the finite-element method, the method of moments, and the finite-difference time-domain method.

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)0.001
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: none
Teacher disagreement score0.699
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

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