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Record W2970775993 · doi:10.1029/2019gl084611

Constraining the Source Regions of Pulsating Auroras

2019· article· en· W2970775993 on OpenAlexaff
Eric Grono, E. Donovan

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMagnetospherePhysicsGeophysicsProtonMagnetosheathAstrophysicsGeologyPlasmaMagnetopauseNuclear physics

Abstract

fetched live from OpenAlex

Abstract Pulsating auroras have often been erroneously discussed as if they are a single phenomenon. For this reason, the relationship between different pulsating auroras is poorly understood. Grono and Donovan (2018, https://doi.org/10.5194/angeo-36-891-2018 ) subcategorized pulsating auroras into amorphous pulsating, patchy pulsating, and patchy auroras, which are separable based on their pulsation and structuring. By comparing the latitudes of these auroras to the location of the proton aurora, we have constrained their source regions for the first time. Pulsating aurora does not occur poleward of the proton aurora. Amorphous pulsating aurora occurs within and equatorward of the proton aurora, while patchy pulsating and patchy auroras predominantly occur equatorward of the optical b2i boundary. This indicates that the characteristic structuring of the patchy auroras is unable to form outside of the mostly dipolar inner magnetosphere, but the wave‐particle interactions that produce auroral pulsations are less constrained, extending into the transition region where the magnetic field begins to stretch.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.291
Teacher spread0.270 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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