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Record W3203693589 · doi:10.1029/2021rs007326

A Comparison of the Topside Electron Density Measured by the Swarm Satellites and Incoherent Scatter Radars Over Resolute Bay, Canada

2021· article· en· W3203693589 on OpenAlexafffundabout
Bion Larson, A. V. Koustov, Alexei Kouznetsov, Levan Lomidze, R. G. Gillies, A. S. Reimer

Bibliographic record

VenueRadio Science · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of CalgaryUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyNational Science Foundation
KeywordsIncoherent scatterElectron densityRadarElectronSatelliteSwarm behaviourComputational physicsPhysicsRemote sensingPlasmaGeodesyIonosphereGeologyGeophysicsMathematicsAstronomyComputer science

Abstract

fetched live from OpenAlex

Abstract Electron density measured at high latitudes by the Swarm satellites is compared with the measurements by the RISR incoherent scatter radars as the satellites fly by the radars' field of views near Resolute Bay, Canada between 2014 and 2019. More than 200 satellite passes crossing multiple radar beams are considered. Overall, the Swarm‐based electron densities are smaller than those measured by the radars by ∼30%. The values are closer to one another at electron densities between and , corresponding to plasma frequencies between 1.5 and 3.5 MHz. Swarm‐measured values are getting progressively smaller than those measured by radars at larger electron densities/plasma frequencies. For the entire range of measured electron densities, the slope of the best fit linear line to the data expressed in terms of electron density is ∼0.62 and offset is . Stronger differences between the instruments were found for observations at nighttime and dawn.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.006
GPT teacher head0.232
Teacher spread0.225 · 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

Citations13
Published2021
Admission routes3
Has abstractyes

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