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Record W2047274202 · doi:10.1063/1.2744226

Energy dissipation via electron energization in standing shear Alfvén waves

2007· article· en· W2047274202 on OpenAlexafffund
P. A. Damiano, Andrew N. Wright, R. D. Sydora, J. C. Samson

Bibliographic record

VenuePhysics of Plasmas · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersScience and Technology Facilities CouncilWestern Canada Research Grid
KeywordsPhysicsField lineElectronDissipationAlfvén waveDipoleEnergy fluxMagnetohydrodynamicsAtomic physicsMagnetic fieldComputational physicsQuantum electrodynamics

Abstract

fetched live from OpenAlex

A two-dimensional hybrid magnetohydrodynamic-kinetic electron model in dipolar coordinates is used to study the case of a fundamental mode toroidal field line resonance (FLR) centered on an L=10 closed dipolar magnetic field line. The model is initialized via a perturbation of the azimuthal shear Alfvén velocity so that only upward field aligned currents (corresponding to downwelling electrons) are present at the ionospheric boundaries during the first half wave period. It is found that the acceleration of the electrons to carry the field aligned currents can be a significant sink of Alfvén wave energy depending on the width of the flux tube. For a FLR with an equatorial perpendicular wavelength of 0.25 RE about 20% of the wave energy is dissipated over a half cycle. This varies inversely with the width of the flux tube increasing to 40% by a width of 0.15 RE, which, unless the system is driven, can completely damp the resonance in about 2–3cycles.

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 score0.002
Threshold uncertainty score0.005

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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

Citations28
Published2007
Admission routes2
Has abstractyes

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