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Record W2950405885 · doi:10.1029/2019ja026851

Color Ratios of Subauroral (STEVE) Arcs

2019· article· en· W2950405885 on OpenAlexaff
S. B. Mende, Charles E. Turner

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersGoddard Space Flight Center
KeywordsExcitationIonWavelengthPhysicsIonizationAtomic physicsOpticsChemistry

Abstract

fetched live from OpenAlex

Abstract Photos of a spectacular optical phenomenon, nicknamed STEVE, show finely structured, purple‐colored, east‐west arcs spanning the sky. These purple Sub‐auroral Arc Emissions are associated with Sub‐Auroral Ion Drifts, often accompanied by separate green arcs frequently displaying magnetic field aligned rays suggesting charge particle excitation. Both types of these arcs and polar auroras appear in some photos. Splitting the images into red, green, and blue channels allowed comparison of color ratios of the three phenomena. Wavelength calibration of the camera verified that the dominant atmospheric auroral emissions, 630.0 nm O( 1 D), O( 1 S) 557.7 nm, and N 2 + 1N bands, were cleanly separated in the red, green, and blue channels of the camera. In the absence of a spectrogram the ratios between the color channels were interpreted in terms of possible excitation mechanisms. The purple arcs contained an excess of blue, presumably N 2 + 1N intensity. This excess production could be due to the excitation of N 2 + ions that were ionized through charge exchange with O + . The green companion arcs appear to be purely green (557.7) with almost no blue and minimal red suggesting excitation by low‐energy electrons excitation at altitudes >100 and <150 km.

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 score0.116
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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

Citations23
Published2019
Admission routes1
Has abstractyes

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