MétaCan
Menu
Back to cohort
Record W3113169168 · doi:10.1029/2019rs006905

Frequency Selection to Avoid Medium Effects on RCS of Conducting Objects With Plane <i>E</i> Wave Polarization

2020· article· en· W3113169168 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

VenueRadio Science · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsLakehead University
Fundersnot available
KeywordsPolarization (electrochemistry)Radar cross-sectionPlane wavePhysicsWavelengthRegular polygonOpticsRadarNear and far fieldPlane (geometry)Computer scienceMathematicsScatteringGeometryTelecommunications

Abstract

fetched live from OpenAlex

Abstract We aim to select the range of frequencies where the medium parameters have less effects on the scattered waves, and as a result we achieve high precision of computed radar cross section (RCS). Ideal object detection can be obtained through calculation of RCS assuming a plane wave incidence in the far field. Numerical results are conducted to investigate effects of medium characteristics and target configuration on its RCS. We postulate convex illumination region of partially convex contour. Targets are taking fairly large sizes in the range of five wavelengths to suit the practical dimensions of objects such as aircraft. In this work, waves propagation from targets in free space and random medium are considered while assuming E polarization of incident wave.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.316

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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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