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Record W2023579944 · doi:10.1109/mwsym.2007.380124

Central-Node Approach for Accurate Self-Adjoint Sensitivity Analysis of Dielectric Structures

2007· article· en· W2023579944 on OpenAlex

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

VenueIEEE MTT-S International Microwave Symposium digest · 2007
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClassification of discontinuitiesDielectricGridPerturbation (astronomy)Sensitivity (control systems)Computer scienceNode (physics)Finite differenceApplied mathematicsMathematical optimizationMathematicsElectronic engineeringMathematical analysisPhysicsGeometryElectrical engineeringEngineeringAcoustics

Abstract

fetched live from OpenAlex

The field solution at the perturbation grid points is needed to perform sensitivity analysis using adjoint approaches. On the other hand, the field solutions provided by time-domain solvers are the least accurate at dielectric interfaces, especially in the case of significant losses. These interfaces are the places where some or all perturbation grid points reside. We propose a central-node approach for the case of dielectric mediums with or without loss. The accuracy of this approach is one order higher than that of our original adjoint approach in the case of dielectric discontinuities, while the computational efficiency remains the same. Verification is carried out through examples using commercial finite-difference time-domain solvers.

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 categoriesMeta-epidemiology (narrow)
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 score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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