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Record W2994798802 · doi:10.1029/2019gl086145

Subauroral Green STEVE Arcs: Evidence for Low‐Energy Excitation

2019· article· en· W2994798802 on OpenAlexaff
S. B. Mende, Brian J. Harding, Charles E. Turner

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersGoddard Space Flight CenterNational Aeronautics and Space Administration
KeywordsExcitationAstrophysicsPhysicsEnergy spectrumFence (mathematics)Emission spectrumArc (geometry)PrecipitationElectron precipitationIonGeologyAtomic physicsGeophysicsSpectral lineAtmospheric sciencesPlasmaMagnetosphereAstronomyMeteorologyGeometryNuclear physics

Abstract

fetched live from OpenAlex

Abstract Subauroral emissions known as STEVEs (Strong Thermal Emission Velocity Enhancements) are sometimes accompanied by green arcs containing magnetic field‐aligned “picket fence” structures. In a newly published spectrum of a green picket fence arc Gillies et al. (2019, https://doi.org/10.1029/2019GL083272 ) showed that the visible emission in such arcs is mostly OI 557.7 nm with minimal N 2 + 1N. This finding is consistent with the color ratios found in digital camera photos (Mende & Turner, 2019, https://doi.org/10.1029/2019JA026851 ) and is distinct from the ratios in auroral precipitation. The spectrum also contains intense N 2 first positive (1P) emission. The presence of OI 557.7 (~4.19 eV excitation energy) and N 2 1P (~7.35 eV), combined with the lack of N 2 + first negative (~18.75 eV) commonly seen in the aurora, suggests that the particles exciting the emission have energy <18.75 eV. This is strong evidence against the precipitation hypothesis recently put forth (Nishimura et al., 2019, https://doi.org/10.1029/2019GL082460 ; Gillies et al., 2019, https://doi.org/10.1029/2019GL083272 ).

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.703

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.038
GPT teacher head0.328
Teacher spread0.290 · 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

Citations53
Published2019
Admission routes1
Has abstractyes

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