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Record W2893487025 · doi:10.1029/2018rs006667

Faraday Rotation, Total Electron Content, and Their Sensitivity to the Average Parallel Component of the Magnetic Field

2018· article· en· W2893487025 on OpenAlexaff
A. C. Cushley, Jean-Marc Noël, К. Кабин

Bibliographic record

VenueRadio Science · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsFaraday effectEarth's magnetic fieldMagnetic fieldPhysicsComputational physicsPolarization (electrochemistry)IonosphereElectronElectron densityField strengthOpticsGeophysicsChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract A plane‐polarized electromagnetic wave that propagates through a plasma, (anti)parallel to a magnetic field, experiences a gradual rotation of its plane of polarization called Faraday rotation (FR). The FR angle depends on the integrated product of the electron density and the strength of the parallel magnetic field projection to the radio wave propagation direction. The integral is taken along the radio wave propagation direction over the entire path length. Therefore, accurate measurements or a suitable model for both the electron density and the magnetic field as well as the propagation trajectory are required for the interpretation of FR measurements. Many authors use the average value of the parallel magnetic field for estimation of FR from ionospheric total electron content measurements. Although it is known that the strength of Earth's geomagnetic field varies slowly at ionospheric altitudes, a reference height characteristic value or mean value may not always be appropriate. This work considers alternative methods to establish a characteristic value for the average parallel component of the magnetic field, particularly when independent FR and total electron content measurements are available.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.206
Teacher spread0.200 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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