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Record W2130436588 · doi:10.1109/radar.2006.1631771

Swathbuckler - Radar System and Signal Processing

2006· article· en· W2130436588 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced SAR Imaging Techniques
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsTestbedComputer scienceRadarSynthetic aperture radarSignal processingSIGNAL (programming language)Emphasis (telecommunications)Compensation (psychology)Real-time computingSystems engineeringTelecommunicationsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Swathbuckler is a multinational initiative to research, build and test an extremely wide swath synthetic aperture radar imaging system. Contributions to the project came from AFRL Rome New York USA (high performance computer (HPC) implementation and Joint Battlespace Infosphere (JBI)), DSTL Malvern UK (high speed data capture and distribution processor (HSDCDP)), and DRDC Ottawa Canada (experimental radar testbed, signal processing algorithm design and test aircraft). This paper describes the Canadian contribution to the Swathbuckler experiment. Particular emphasis is placed on the architecture of the experimental airborne radar and the high-level design of the motion compensation and signal processing algorithms. Companion papers provide a complete Swathbuckler overview, details on the HSDCDP, details on the HPC implementation and the utilization of the JBI, and finally results from the flight tests in Ottawa.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.289

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 head0.004
GPT teacher head0.199
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

Quick stats

Citations5
Published2006
Admission routes2
Has abstractyes

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