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Record W4307689925 · doi:10.3847/1538-4357/ac9404

Linear and Nonlinear Kelvin–Helmholtz Instability and Magnetohydrodynamic Wave Emission in Sheared Astrophysical Plasma Flows

2022· article· en· W4307689925 on OpenAlexfundno aff
H. Turkakin, I. R. Mann, R. Rankin

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersCanadian Space AgencyNatural Sciences and Engineering Research Council of CanadaNational Nuclear Security AdministrationOffice of ScienceUniversity of RochesterU.S. Department of Energy
KeywordsPhysicsMagnetohydrodynamicsMagnetohydrodynamic driveInstabilityShear flowPlasmaMechanicsAstrophysicsAlfvén waveClassical mechanicsComputational physics

Abstract

fetched live from OpenAlex

Abstract The evolution of the Kelvin–Helmholtz instability (KHI) and magnetohydrodynamic (MHD) wave emission is investigated at shear-flow boundaries of magnetized plasmas. While MHD wave emission has been suggested to be only possible during the nonlinear stages, we find that there is also significant wave emission during the KHI’s linear stages. These emitted MHD waves may have stronger impacts than KHI surface waves since they can act to transport energy away from the local region of the shear flow. The removal of energy from the shear-flow region, instead of just the local redistribution considered in previous studies, and its propagation away from the interface could have major implications for the evolution of astrophysical objects characterized by fast plasma flow shears.

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
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.208
Teacher spread0.202 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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