MétaCan
Menu
Back to cohort
Record W3143820165 · doi:10.1109/tap.2021.3070153

High-Frequency Radar Cross Section of the Ocean Surface With Arbitrary Roughness Scales: Higher Order Corrections and General Form

2021· article· en· W3143820165 on OpenAlexafffund
Murilo T. Silva, Weimin Huang, Eric W. Gill

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRadar cross-sectionSurface (topology)Surface roughnessRadarPhysicsCross section (physics)Wind waveSurface waveOpticsBragg's lawGeologyGeometryMathematicsScatteringComputer science

Abstract

fetched live from OpenAlex

The present work shows the derivation of general forms for the expressions of the first- and second-order corrections to the radar cross section (RCS) of the ocean surface at electromagnetically high sea states. An analysis of the morphology of the correction terms and their impact on the total RCS of the ocean surface is presented. It is shown that most of the visible impact on the total RCS of the ocean surface is due to first-order hydrodynamic terms and is concentrated between the Bragg peaks. Also, second-order hydrodynamic correction terms can increase the integral over the second-order region outside the dominant Bragg peak by up to 30% at extreme ocean conditions. Although comparison with field data was not conclusive, the presented results can improve the representation of electromagnetically large waves in the total RCS of the ocean surface without dismissing the analysis methods for height-restricted RCSs presented in the literature.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.386

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 studies0.0010.000
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 head0.009
GPT teacher head0.201
Teacher spread0.193 · 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 designObservational
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

Citations5
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Antennas and PropagationSame topicOcean Waves and Remote SensingFrench-language works237,207