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Record W2563821119 · doi:10.1002/2016ja022816

Emission of magnetosound from MHD‐unstable shear flow boundaries

2016· article· en· W2563821119 on OpenAlexafffund
H. Turkakin, R. Rankin, I. R. Mann

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersCanadian Space Agency
KeywordsMagnetohydrodynamicsPhysicsMagnetopauseGeophysicsMagnetosphereMagnetic fieldMechanicsAlfvén waveComputational physics

Abstract

fetched live from OpenAlex

Abstract The emission of propagating MHD waves from the boundaries of flow channels that are unstable to the Kelvin‐Helmholtz Instability (KHI) in magnetized plasma is investigated. The KHI and MHD wave emission are found to be two competing processes. It is shown that the fastest growing modes of the KHI surface waves do not coincide with efficient wave energy transport away from a velocity shear boundary. MHD wave emission is found to be inefficient when growth rates of KHI surface waves are maximum, which corresponds to the situation where the ambient magnetic field is perpendicular to the flow channel velocity vector. The efficiency of wave emission increases with increasing magnetic field tension, which in Earth's magnetosphere likely dominates along the nightside magnetopause tailward of the terminator, and within earthward Bursty Bulk Flows (BBFs) in the inner plasma sheet. MHD wave emission may also dominate in Supra‐Arcade Downflows (SADs) in the solar corona. Our results suggest that efficient emission of propagating MHD waves along BBF and SAD boundaries can potentially explain observations of deceleration and stopping of BBFs and SADs.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

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