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Record W2793564039 · doi:10.1002/2017gl076051

Alfvénic Dynamics and Fine Structuring of Discrete Auroral Arcs: Swarm and e‐POP Observations

2018· article· en· W2793564039 on OpenAlexafffund
David M. Miles, I. R. Mann, I. P. Pakhotin, J. K. Burchill, Andrew Howarth, D. J. Knudsen, R. L. Lysak, D. D. Wallis, L. L. Cogger, A. W. Yau

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsMagna International (Canada)University of CalgaryUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyEuropean Space AgencyUniversity of Iowa
KeywordsPhysicsIonosphereSwarm behaviourGeophysicsSpacecraftOutflowMagnetic fieldMagnetosphereComputational physicsElectric fieldMeteorologyAstronomy

Abstract

fetched live from OpenAlex

Abstract The electrodynamics associated with dual discrete arc aurora with antiparallel flow along the arcs were observed nearly simultaneously by the enhanced Polar Outflow Probe (e‐POP) and the Swarm A and C spacecraft. Auroral imaging from e‐POP reveals 1–10 km structuring of the arcs, which move and evolve on second timescales and confound the traditional single‐spacecraft field‐aligned current algorithms. High‐cadence magnetic data from e‐POP show 1–10 Hz, inferred Alfvénic, perturbations coincident with and at the same scale size as the observed dynamic auroral fine structures. High‐cadence electric and magnetic field data from Swarm A reveal nonstationary electrodynamics involving reflected and interfering Alfvén waves and modulation consistent with trapping in the ionospheric Alfvén resonator (IAR). These observations suggest a role for Alfvén waves, perhaps also the IAR, in discrete arc dynamics on 0.2–10 s timescales and ~1–10 km spatial scales and reinforce the importance of considering Alfvén waves in magnetosphere‐ionosphere coupling.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.293
Teacher spread0.271 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations44
Published2018
Admission routes2
Has abstractyes

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