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Record W4296448755 · doi:10.1029/2022ja030896

NRLMSIS 2.1: An Empirical Model of Nitric Oxide Incorporated Into MSIS

2022· article· en· W4296448755 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Waterloo
FundersOffice of Naval Research
KeywordsZenithSolar zenith angleExtant taxonAtmospheric sciencesEmpirical modellingAltitude (triangle)Environmental scienceMeteorologyEarth's magnetic fieldAtmospheric modelsLatitudeAtmosphere (unit)MathematicsPhysicsGeodesyComputer scienceGeologySimulationGeometry

Abstract

fetched live from OpenAlex

Abstract We have developed an empirical model of nitric oxide (NO) number density at altitudes from ∼73 km to the exobase, as a function of altitude, latitude, day of year, solar zenith angle, solar activity, and geomagnetic activity. The model is part of the NRLMSIS® 2.1 empirical model of atmospheric temperature and species densities; this upgrade to NRLMSIS 2.0 consists solely of the addition of NO. MSIS 2.1 assimilates observations from six space‐based instruments: UARS/HALOE, SNOE, Envisat/MIPAS, ACE/FTS, Odin/SMR, and AIM/SOFIE. We additionally evaluated the new model against independent extant NO data sets. In this paper, we describe the formulation and fitting of the model, examine biases between the data sets and model and among the data sets, compare with another empirical NO model (NOEM), and discuss scientific aspects of our analysis.

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.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.084
GPT teacher head0.349
Teacher spread0.265 · 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