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Auroral Scintillation Monitoring for GNSS

2018· article· en· W2893461580 on OpenAlexaffabout
S. Skone, Maryam Najmafshar, S. C. Mushini, E. Spanswick

Bibliographic record

Venue2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGNSS applicationsSatellite systemScintillationRemote sensingSpace weatherSatelliteInterplanetary scintillationEnvironmental scienceComputer scienceIonosphereMeteorologySatellite navigationGeographyGlobal Positioning SystemTelecommunicationsGeologyPhysicsAerospace engineeringGeophysicsEngineeringDetector

Abstract

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Auroral precipitation and associated electric currents affect accuracy of practical systems and services: e.g. global navigation satellite systems (GNSS), communication systems, and power systems. Such space weather hazards are important for Canadians due to increasing civilian and military activity in the Arctic, and increasing reliance on GNSS in the decade ahead. Ionospheric scintillation associated with the diffuse and discrete aurora can be particularly problematic for safety-critical operations. In order to better study, model and mitigate such effects, the University of Calgary leads the Transition Region Explorer (TREx) - the world's foremost auroral imaging facility for remote sensing the near-earth space environment.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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