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Record W2795845390 · doi:10.1002/9781119324522.ch17

Birkeland Currents at Mercury

2018· other· en· W2795845390 on OpenAlexaff
B. J. Anderson, C. L. Johnson, H. Korth, L. Philpott

Bibliographic record

VenueGeophysical monograph · 2018
Typeother
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMagnetosphereConvectionPhysicsGeophysicsIonosphereSubstormPlanetPlasmaspherePlasma sheetAtmospheric electricityPlasmaAtmospheric sciencesElectric fieldAstrophysicsMechanics

Abstract

fetched live from OpenAlex

Birkeland currents are present at both Earth and Mercury, and differences in these currents reflect fundamental differences in the convection dynamics of these systems. At Earth, the conductive ionosphere and the high altitude magnetosphere are linked with these currents through the Pedersen conductance, which closes the currents in the ionosphere, and through magnetospheric plasma, which carries the Region 2 currents between the evening and morning sectors while shielding the inner magnetosphere from the convection potential. The currents reflect the convection of magnetic flux from the dayside, over the polar caps into the magnetotail, and subsequently sunward in the tail to the dayside. At Mercury, the analysis indicates that the Birkeland currents close through the planet itself with at least half of the current closing through the core. There is no evidence of Region 2 currents at Mercury, implying that the magnetosphere and planet itself are not shielded from the convection cycle and suggesting that the planet also participates in the return convection although it is not known how this is actually accomplished. Future exploration of Mercury making measurements of the plasma flow and electric fields may resolve some of the basic questions about how the convection cycle closes at Mercury.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.003

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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