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Record W2112711787 · doi:10.1109/igarss.1995.520243

Operational use of RADARSAT SAR for marine monitoring and surveillance

2002· article· en· W2112711787 on OpenAlexaffabout
Richard B. Olsen, P. Bugden, Y. Andrade, P A Hoyt, Marlon R. Lewis, H. Edel, C Bjerkelund

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsAtlantic School of Theology
Fundersnot available
KeywordsRemote sensingWorkstationSea iceSatelliteSynthetic aperture radarSea stateFeature (linguistics)Computer scienceEnvironmental scienceMeteorologyGeologyGeographyEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

RADARSAT will be the first spaceborne SAR mission planned for operational use. Primary operational applications will be monitoring of sea ice, ice bergs, sea state, ocean surface features, coastal processes and ship activity. A dedicated workstation system, the Ocean Feature Workstation, has been designed and implemented to perform routine operational analysis of SAR ocean imagery for extraction of surface feature information, wave data and positions of vessels. The extracted information is compiled as small information product files for rapid distribution to end users. The system will be installed at Gatineau Satellite Station in August 1995.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.260
Teacher spread0.190 · 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.

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

Citations8
Published2002
Admission routes2
Has abstractyes

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