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Record W2594404036

Membrane antenna for sar satellite

2002· article· en· W2594404036 on OpenAlexaffabout
Guy Séguin, Tony Pellerin, Jerome Colinas, Arthur Baylis, Nicholas Audet, Luís Martins Camelo, Peter Wood

Bibliographic record

VenueInternational Symposium on Antenna Technology and Applied Electromagnetics · 2002
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsTransCanada (Canada)Canadian Space Agency
Fundersnot available
KeywordsPayload (computing)SpacecraftAntenna (radio)SatelliteRemote sensingSynthetic aperture radarAerospace engineeringEnvelope (radar)Computer scienceElectrical engineeringEngineeringGeologyRadar
DOInot available

Abstract

fetched live from OpenAlex

The latest generation of SAR satellites, such as RADARSAT-2, carry a large SAR payload with a mass of almost 850 kg which occupies a stowed envelope close to seven cubic meters. Antenna mass and stowed envelope are important drivers in the choice of the size of a spacecraft, as well as in the choice of a launcher. A SAR membrane antenna offers the possibility of realizing extremely lightweight, large aperture antennas having a very small stowed volume (less than 250 kg payload mass, less than one cubic meter stowed volume). This type of antenna could be implemented on a small satellite at a much lower cost. Such a SAR membrane antenna is being developed by EMS Technologies with the support of the Canadian Space Agency (CSA).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score1.000

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)0.0000.000

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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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 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

Citations1
Published2002
Admission routes2
Has abstractyes

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