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Record W2086155586 · doi:10.1002/2014gl062300

Ten years of Martian nitric oxide nightglow observations

2015· article· en· W2086155586 on OpenAlexaff
Arnaud Stiepen, Jean‐Claude Gérard, Marie‐Ève Gagné, Franck Montmessin, Jean‐Loup Bertaux

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Victoria
FundersBelgian Federal Science Policy OfficeEuropean Space Agency
KeywordsAirglowMartianOccultationAtmospheric sciencesBrightnessAtmosphere (unit)Atmosphere of MarsMars Exploration ProgramRadio occultationLongitudeLatitudeAltitude (triangle)Environmental scienceScale heightPhysicsAstrobiologyAstronomyIonosphereMeteorology

Abstract

fetched live from OpenAlex

Abstract We present 10 years of Martian NO nightglow Spectroscopy for Investigation of Characteristics of the Atmosphere of Mars observations in limb and stellar occultation modes. The NO nightglow is used as a tracer of the summer‐to‐winter hemispherical circulation in the upper atmosphere of Mars. Its distribution roughly follows the curve latitude = −80 sin(solar longitude), with deviations. We find that the peak brightness is 5 ± 4.5 kR, situated at 72 ± 10.4 km. It ranges from 0.23 to 18.51 kR and from 42 to 97 km. These values are consistent with previous studies. We also present maps of the brightness of the NO emission peak and its variability, an important factor that can reach up to 50% of the emission and is not reproduced by average brightness model maps. The characteristics and factors that may control the emission are investigated. In particular, we show that the solar activity exerts a positive influence on the number of detections. It does not influence, on the contrary, the brightness or altitude of the peak of the NO nightglow emission. Results presented in this study lead to future comparisons with global Martian atmospheric models and observational targets for the Imaging Ultraviolet Sprectrograph Mars Atmosphere and Volatile Evolution.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.092
GPT teacher head0.309
Teacher spread0.217 · 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.

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

Citations34
Published2015
Admission routes1
Has abstractyes

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