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Record W4238667245 · doi:10.23919/oceans.2015.7401877

The second-order bistatic high frequency radar scattering cross section of the ocean surface for the case of floating platform

2015· article· en· W4238667245 on OpenAlexaff
Yue Ma, Weimin Huang, Eric W. Gill

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBistatic radarRadar cross-sectionPhysicsRadarAntenna (radio)Cross section (physics)Radar imagingRadar engineering detailsAcousticsOpticsScatteringComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The second-order bistatic high frequency radar cross section of ocean surface is derived for the case of a fixed receiver and a floating transmitter. The second-order radar cross section contains both the hydrodynamic contribution and the electromagnetic contribution. The second-order hydrodynamic contribution is obtained based on the first-order bistatic model with antenna motion. The derivation of the second-order electromagnetic contribution begins with a general expression for the bistatically received second-order electric field for the case of floating antenna. A new bistatic electromagnetic coupling coefficient, which unlike some earlier versions produces no nonphysical singularities in the radar cross section, is derived. The new radar cross section model is simulated and compared with that of monostatic case. The motion-induced second-order peaks appearing in the spectrum are seen to have significantly less energy than those in the first-order case.

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)0.001
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 score0.333
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.240
Teacher spread0.216 · 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 designSimulation or modeling
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

Citations2
Published2015
Admission routes1
Has abstractyes

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