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Record W2077072444 · doi:10.1029/2010ja015736

Modeling the relationship between substorm dipolarization and dispersionless injection

2011· article· en· W2077072444 on OpenAlexafffund
К. Кабин, E. Spanswick, R. Rankin, E. Donovan, J. C. Samson

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of AlbertaUniversity of CalgaryRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSubstormPhysicsElectronIonosphereRiometerGeophysicsAdiabatic processPlasma sheetPlasmaMagnetosphereComputational physicsAtomic physics

Abstract

fetched live from OpenAlex

[1] Significant populations of electrons with energies of tens of keV appear in the Earth's inner central plasma sheet during the substorm expansion phase. Increasing observational evidence indicates that these injections begin at a radially narrow but azimuthally extended transition between very stretched and less stretched field lines around 8 RE. In this work we suggest that the tailward retreat of this transition region can be responsible for adiabatic acceleration of electrons which is sufficient to cause ionospheric signatures of the dispersionless injections observed by riometers. To support this mechanism we develop a novel conceptual magnetotail magnetic field model with a few adjustable parameters which can be easily constrained by observations. Our calculations show that a tailward motion of the transition region at the speed of 0.8 RE/min is required to achieve good agreement with riometer observations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.064
GPT teacher head0.312
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 designSimulation or modeling
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

Citations6
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Geophysical Research Atmospheres→Same topicIonosphere and magnetosphere dynamics→French-language works237,207→