MétaCan
Menu
Back to cohort
Record W2163520949 · doi:10.1109/tmag.2006.871389

Scattering from dielectric and metallic bodies using a high-order, Nystrom, multilevel fast mutipole algorithm

2006· article· en· W2163520949 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 Transactions on Magnetics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsMultipole expansionScatteringDielectricIntegral equationSquare (algebra)Computational electromagneticsNyström methodComputer scienceOrder (exchange)Computational physicsAlgorithmPhysicsMathematicsOpticsMathematical analysisGeometryElectromagnetic fieldQuantum mechanics

Abstract

fetched live from OpenAlex

The multilevel fast multipole algorithm (MLFMA) is an established way to accelerate the solution of the integral equations governing scattering of electromagnetic waves. Another way is to use high-order methods, of which the locally corrected Nystrom (LCN) method is, perhaps, the best; it has been applied to metallic scatterers up to order 10. In this paper, the technique (MLFMA + LCN) is extended to handle mixed conducting/dielectric bodies. Results for coated circular and square cylinders, using orders up to 8, demonstrate the efficiency of the 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.709
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
Bibliometrics0.0000.000
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 head0.216
Teacher spread0.207 · 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