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Record W2782210158

Bistatic observations of the ocean surface with HF radar, satellite and airborne receivers

2017· article· en· W2782210158 on OpenAlexaff
P. A. Bernhardt, C. L. Siefring, Stanley C. Briczinski, Juha Vierinen, E. S. Miller, Andrew Howarth, H. G. James, Eugene Blincoe

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRemote sensingSatelliteGeologyRadarWave radarSurface waveWind waveRadio waveSea-surface heightOcean surface topographyBistatic radarMeteorologyRadar imagingGeodesyGeographyPhysicsOceanographyOpticsAltimeterComputer scienceTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

A new concept has been developed which can view vast regions of the Earth's surface. Ground HF transmissions are reflected by the ionosphere to illuminate the ocean over a few thousand kilometers. HF receivers detect the radio waves scattered by the sea and land surface. Using the theory of radio wave scatter from ocean surfaces, the HF data is then processed to yield the directional wave-height spectrum of the ocean. This technique has several advantages over existing remote sensing methods. A large area of the ocean can be sampled to yield the wave-height characteristics with high, km-scale resolution. The wave height spectrum can be directly compared with temporal frequency spectrum obtained with buoys at specific points in the ocean volume. Furthermore, the technique uses HF waves which penetrate the dense rain found in hurricanes.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.998

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 studies0.0010.002
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 head0.043
GPT teacher head0.238
Teacher spread0.195 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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