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Record W1875527434 · doi:10.1109/aps.2001.958925

Beam array scattering by wedges and rectangular cylinders

2002· article· en· W1875527434 on OpenAlexaff
H.D. Cheung, E.V. Jull

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAperture (computer memory)OpticsScatteringDiffractionAngular aperturePhysicsBeam divergenceOmnidirectional antennaBeam (structure)Radiation patternNear and far fieldBeam diameterAntenna (radio)Focal lengthAcousticsComputer scienceLens (geology)Telecommunications

Abstract

fetched live from OpenAlex

Scattering by an obstacle in the near field of a radiating aperture can be obtained by superimposing many much simpler omnidirectional scattering solutions. These sources must be closely spaced in the aperture with relative amplitudes corresponding to the aperture field distribution. Highly accurate results can also be obtained with fewer basis solutions if they are beam solutions with the beams arranged in a Gabor lattice. Beam solutions are obtained from omnidirectional source solutions by substituting appropriate complex source coordinates for the real source coordinates. This procedure has already been used for antenna aperture scattering by local half planes and wide slits, where the main results are for forward scattered fields, and also for rectangular cylinders where backscattered fields are also shown. Back radiation from an aperture depends on aperture edge diffraction. This is not specified in a beam array representation, so the total backscattered field cannot be known. Here we revisit earlier solutions to determine how seriously back radiation from the aperture affects the numerical results and to improve our representation of both the radiation fields of an aperture in isolation and the total back scattered fields of an obstacle in the vicinity of the aperture.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.437

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 head0.012
GPT teacher head0.172
Teacher spread0.160 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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