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Record W1680230107 · doi:10.1109/igarss.1995.523995

On-board encoding of the ENVISAT wave mode data

2002· article· en· W1680230107 on OpenAlexaff
I.H. McLeod, I. Cumming

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSynthetic aperture radarData reductionComputer scienceRemote sensingSatelliteQuantization (signal processing)Mode (computer interface)Reduction (mathematics)Radar imagingRadarElectronic engineeringAlgorithmArtificial intelligenceGeologyData miningTelecommunicationsEngineeringMathematics

Abstract

fetched live from OpenAlex

The synthetic aperture radar sensor on the ENVISAT remote sensing satellite will utilize a data reduction system called Flexible Block Adaptive Quantization (FBAQ). This technology will allow the 8 bits/sample SAR signal data to be reduced to 4, 3, or 2 bits/sample, as specified by the mission controller. For wave mode operation, in which small SAR "vignettes" are acquired over oceanic regions, the 8 to 2 bits/sample mode of FBAQ must be employed due to on-board storage limitations. The authors quantitatively evaluate the effect of the FBAQ data reduction on the power spectra of the vignettes, obtained using ESA wave mode processing methods. Using ERS-1 SAR signal data modified to reflect the properties of ENVISAT SAR data, the authors show that the use of the 2-bit FBAQ algorithm will yield power spectra results better than those currently available from ERS-1, with the degree of improvement dependent on the distribution shape of the SAR signal data and the radiometric variation within the vignette.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.114
GPT teacher head0.232
Teacher spread0.118 · 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

Citations11
Published2002
Admission routes1
Has abstractyes

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