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Record W2800856574 · doi:10.1029/2017ja024405

On the Persistent Shape and Coherence of Pulsating Auroral Patches

2018· article· en· W2800856574 on OpenAlexafffund

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNorges Forskningsråd
KeywordsCoherence (philosophical gambling strategy)ConvectionSpatial coherenceSatelliteRange (aeronautics)

Abstract

fetched live from OpenAlex

Abstract The pulsating aurora covers a broad range of fluctuating shapes that are poorly characterized. The purpose of this paper is therefore to provide objective and quantitative measures of the extent to which pulsating auroral patches maintain their shape, drift and fluctuate in a coherent fashion. We present results from a careful analysis of pulsating auroral patches using all‐sky cameras. We have identified four well‐defined individual patches that we follow in the patch frame of reference. In this way we avoid the space‐time ambiguity which complicates rocket and satellite measurements. We find that the shape of the patches is remarkably persistent with 85–100% of the patch being repeated for 4.5–8.5 min. Each of the three largest patches has a temporal correlation with a negative dependence on distance, and thus does not fluctuate in a coherent fashion. A time‐delayed response within the patches indicates that the so‐called streaming mode might explain the incoherency. The patches appear to drift differently from the SuperDARN‐determined convection velocity. However, in a nonrotating reference frame the patches drift with 230–287 m/s in a north eastward direction, which is what typically could be expected for the convection return flow.

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)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.039
GPT teacher head0.317
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 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

Citations9
Published2018
Admission routes2
Has abstractyes

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