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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

fetched live from OpenAlex

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
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 source (direct Gemma or distilled Codex), not a consensus.

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