MétaCan
Menu
Back to cohort
Record W2886772604 · doi:10.1109/mwsym.2018.8439340

Efficient Sensitivity Analysis of Microwave Structures with Multiple Design Parameters in FDTD

2018· article· en· W2886772604 on OpenAlex
Kae-An Liu, Costas D. Sarris

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 institutionsUniversity of Toronto
Fundersnot available
KeywordsFinite-difference time-domain methodElectromagnetic fieldMultiphysicsField (mathematics)MicrowaveComputer scienceBandwidth (computing)Finite difference methodGridComputational electromagneticsApplied mathematicsMathematicsElectronic engineeringMathematical analysisFinite element methodPhysicsOpticsEngineeringGeometryTelecommunications

Abstract

fetched live from OpenAlex

Exploiting the structure of the Finite-Difference Time-Domain (FDTD) update equations, a direct method to compute electromagnetic field derivatives with respect to multiple design parameters is derived. This method is based on recursively computing field derivatives up to any order n, by simulating the original unperturbed FDTD grid, excited by equivalent sources that depend on field derivatives of order zero to n-1. Derivatives with respect to any other field-based function of interest (such as scattering parameters or multiphysics quantities) can be easily commuted, over the whole bandwidth of an FDTD simulation.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.253

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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