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Record W3094544861 · doi:10.5140/jass.2020.37.3.209

Initial Operation and Preliminary Results of the Instrument for the Study of Stable/Storm-Time Space (ISSS) on Board the Next Generation Small Satellite-1 (NEXTSat-1)

2020· article· en· W3094544861 on OpenAlexaff
Eojin Kim, Ji‐Hyeon Yoo, Hee‐Eun Kim, Hoonkyu Seo, Kwangsun Ryu, Jongdae Sohn, Junchan Lee, Jongho Seon, Ensang Lee, Dae‐Young Lee, Kyoung‐Wook Min, Kyung-In Kang, SangYun Lee, Juneseok Kang

Bibliographic record

VenueJournal of Astronomy and Space Sciences · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsYork University
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaNational Research Foundation
KeywordsSpacecraftSatelliteOn boardRemote sensingOrbit (dynamics)Aerospace engineeringOrbital mechanicsStormScientific instrumentSpace weatherComputer scienceUniversal TimeOrbital inclinationMeteorologyPhysicsAstronomyGeologyEngineeringMathematics

Abstract

fetched live from OpenAlex

This paper describes the initial operations and preliminary results of the Instrument for the study of Stable/Storm-time Space (ISSS) onboard the microsatellite Next Generation Small Satellite-1 (NEXTSat-1), which was launched on December 4, 2018 into a sun-synchronous orbit at an altitude of 575 km with an orbital inclination angle of 97.7°. The spacecraft and the instruments have been working normally, and the results from the observations are in agreement with those from other satellites. Nevertheless, improvement in both the spacecraft/instrument operation and the analysis is suggested to produce more fruitful scientific results from the satellite operations. It is expected that the ISSS observations will become the main mission of the NEXTSat-1 at the end of 2020, when the technological experiments and astronomical observations terminate after two years of operation.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.052
GPT teacher head0.259
Teacher spread0.207 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2020
Admission routes1
Has abstractyes

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