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Record W1961265850 · doi:10.1109/aps.2005.1551948

Semi-analytical approach for sensitivity analysis with lossy dielectrics

2005· article· en· W1961265850 on OpenAlex
S.M. Ali, Natalia K. Nikolova, Mohamed H. Bakr

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLossy compressionSensitivity (control systems)Extension (predicate logic)SolverComputer scienceFrequency domainAlgorithmDielectricVariable (mathematics)Matrix (chemical analysis)Applied mathematicsMathematical optimizationMathematicsElectronic engineeringMathematical analysisEngineeringMaterials science

Abstract

fetched live from OpenAlex

We propose an extension of the adjoint variable method for design sensitivity analysis to problems involving lossy materials. We first extend a recently developed discrete algorithm, which was originally applied to loss-free problems. It requires the solution of a stepwise perturbed structure that is available only approximately. Then, we enhance this algorithm by proposing a semi-analytical approach. The approach requires the solution of the unperturbed structure, which is readily available. It employs the analytical dependence of the system matrix on the material properties of the structure. All responses and their sensitivities are obtained through two system analyses. We consider applications with a frequency-domain solver based on the transmission line method (FDTLM).

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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