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Record W2047334176 · doi:10.1109/lgrs.2007.900698

Remote Sensing of 3-D Conducting Objects in a Layered Medium Using Electromagnetic Surface Waves

2007· article· en· W2047334176 on OpenAlexaff
Marius Birsan

Bibliographic record

VenueIEEE Geoscience and Remote Sensing Letters · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsCylinderAcousticsElectrical conductorSeabedElectromagnetic fieldSurface waveGeologyElectromagnetic radiationHalf-spaceRemote sensingOpticsPhysicsGeometry

Abstract

fetched live from OpenAlex

Antennas that are located on or near the boundary between two electrically different media, such as air and earth, or seawater and rock, are used as prospective tools for remote sensing and geophysical exploration. As an example, this letter examines the electromagnetic (EM) response of a metallic object that is submerged in a conducting layer of seawater that is situated between an infinite half-space of air and a seabed of lower electrical conductivity. When the source and the object are at some distance away in the water, the primary EM propagation mode is on the interfaces because the surface waves are less attenuated than those following the direct or reflected propagation paths. The simulation tool that predicts the performances of the EM detection system uses the method-of-moments integral equation technique. The method is validated and applied to calculate the scattered fields from a submerged perfectly conducting cylinder. The numerical results are then compared with experimental data that are obtained by towing a steel cylinder through an impressed field that is produced by a horizontal electric source.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.258
Teacher spread0.238 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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