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Record W3027879809

New Insights about Meridional Circulation Dynamics from 3D MHD Global Simulations of Solar Convection and Dynamo Action

2016· article· en· W3027879809 on OpenAlexfundno aff
Dário Passos, Paul Charbonneau, Mark S. Miesch

Bibliographic record

VenueSapientia (Algarve University) · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCompute CanadaNational Science Foundation
KeywordsDynamoMagnetohydrodynamicsConvectionAction (physics)PhysicsSolar dynamoCirculation (fluid dynamics)Atmospheric sciencesConvection zoneGeophysicsDynamo theoryClimatologyMechanicsGeologyMagnetic field
DOInot available

Abstract

fetched live from OpenAlex

The solar meridional circulation is a "slow", large scale flow that transports magnetic field and plasma throughout the convection zone in the (r, theta) plane and plays a crucial role in controlling the magnetic cycle solutions presented by flux transport dynamo models. Observations indicate that this flow speed varies in anti-phase with the solar cycle at the solar surface. A possible explanation for the source of this variation is based on the fact that inflows into active regions alter the global surface pattern of the meridional circulation. In this work we examine the meridional circulation profile that emerges from a 3D global simulation of the solar convection zone, and its associated dynamics. We find that at the bottom of the convection zone, in the region where the toroidal magnetic field accumulates, the meridional circulation is highly modulated through the action of a magnetic torques and thus provides evidence for a new mechanism to explain the observed cyclic variations.

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 score0.013
Threshold uncertainty score0.026

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 science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.198
Teacher spread0.192 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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