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Record W2317211559 · doi:10.2514/6.2013-123

GPS Results for the Radio Aurora Explorer II CubeSat Mission

2013· article· en· W2317211559 on OpenAlexfundno aff
Jessica Arlas, Sara Spangelo

Bibliographic record

Venue51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition · 2013
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of MichiganNational Science Foundation
KeywordsCubeSatGlobal Positioning SystemComputer scienceSatelliteOrbit determinationRemote sensingAssisted GPSOrbit (dynamics)Precision Lightweight GPS ReceiverTime to first fixGPS disciplined oscillatorGeodesyReal-time computingGPS signalsAerospace engineeringGps receiverGeographyTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper presents the performance of the Global Positioning System (GPS) subsystem for the Radio Aurora eXplorer II (RAX-2) CubeSat mission. The GPS subsystem is required to satisfy the science mission objectives to study space weather. In particular, the GPS subsystem must provide accurate spatial and temporal data. To verify the mission requirements and assess GPS subsystem performace in on-orbit conditions, we assess the carrier-to-noise ratio and position accuracy. Additionally, we study the accuracy of the current method of orbit tracking by comparing the orbital elements from Two Line Element sets to the RAX-2 GPS data. The results presented confirm functionality of the GPS subsystem and provide useful information for future small satellite teams considering flying a GPS.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.251
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2013
Admission routes1
Has abstractyes

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