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Record W2971791208 · doi:10.1029/2019gl084473

The Vertical Distribution of the Optical Emissions of a Steve and Picket Fence Event

2019· article· en· W2971791208 on OpenAlexaff
William Archer, J.‐P. St.‐Maurice, Bea Gallardo‐Lacourt, G. W. Perry, C. M. Cully, E. Donovan, D. M. Gillies, R. Downie, Joseph P. Smith, D. Eurich

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsWestern UniversityGovernment of AlbertaUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsPicketingFence (mathematics)Altitude (triangle)GeologyEvent (particle physics)PhysicsLawPolitical scienceAstrophysicsEngineeringGeometry

Abstract

fetched live from OpenAlex

Abstract So‐called “Steve” subauroral purple emissions have recently been uncovered by auroral photographers and have rapidly become an intense subject of debate as to their origin. In some events, nearby periodic green emissions have also been uncovered and given the name “picket fence,” owing to their appearance. The present paper advances our understanding of these phenomena by narrowing down the altitude extent of the Steve and picket fence emissions. Our determination is based on the event of 16 September 2017, which was simultaneously observed from two vantage points, allowing for a determination of the height range of Steve and picket fence through triangulation. We show that the picket fence extend between 95‐ and 150‐km altitude and is aligned with the geomagnetic field, while the Steve altitude spread is between 130 and 270 km. We also show the two phenomena to be on nearby or perhaps the same magnetic field lines.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.188

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 head0.010
GPT teacher head0.278
Teacher spread0.268 · 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 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

Citations63
Published2019
Admission routes1
Has abstractyes

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