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Record W4200191074 · doi:10.1029/2021gl096583

Unsteady Magnetopause Reconnection Under Quasi‐Steady Solar Wind Driving

2021· article· en· W4200191074 on OpenAlexaff
Ying Zou, Brian M. Walsh, Li‐Jen Chen, Jonathan Ng, Xueling Shi, Chih‐Ping Wang, L. R. Lyons, Jiang Liu, V. Angelopoulos, K. A. McWilliams, J. M. Ruohoniemi

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Saskatchewan
FundersAir Force Research LaboratoryAir Force Office of Scientific ResearchNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsMagnetopauseMagnetosheathPhysicsMagnetic reconnectionSolar windGeophysicsMagnetosphereAmplitudeElectric fieldComputational physicsMagnetic field

Abstract

fetched live from OpenAlex

The intrinsic temporal nature of magnetic reconnection at the magnetopause has been an active area of research. Both temporally steady and intermittent reconnection have been reported. We examine the steadiness of reconnection using space-ground conjunctions under quasi-steady solar wind driving. The spacecraft suggests that reconnection is first inactive, and then activates. The radar further suggests that after activation, reconnection proceeds continuously but unsteadily. The reconnection electric field shows variations at frequencies below 10 mHz with peaks at 3 and 5 mHz. The variation amplitudes are ∼10-30 mV/m in the ionosphere, and 0.3-0.8 mV/m at the equatorial magnetopause. Such amplitudes represent 30%-60% of the peak reconnection electric field. The unsteadiness of reconnection can be plausibly explained by the fluctuating magnetic field in the turbulent magnetosheath. A comparison with a previous global hybrid simulation suggests that it is the foreshock waves that drive the magnetosheath fluctuations, and hence modulate the reconnection.

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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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

Citations20
Published2021
Admission routes1
Has abstractyes

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Same venueGeophysical Research LettersSame topicIonosphere and magnetosphere dynamicsFrench-language works237,207