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Record W2951720957 · doi:10.5194/amt-12-3111-2019

Validation of Solar Occultation for Ice Experiment (SOFIE) nitric oxide measurements

2019· article· en· W2951720957 on OpenAlexafffund
Mark E. Hervig, B. T. Marshall, S. M. Bailey, D. E. Siskind, James M. Russell, Charles Bardeen, Kaley A. Walker, B. Funke

Bibliographic record

VenueAtmospheric measurement techniques · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Toronto
FundersNuclear Safety and Security CommissionCanadian Space AgencyOld Dominion UniversityUniversity of WaterlooHeliophysics DivisionNational Aeronautics and Space Administration
KeywordsSunriseSunsetOccultationAtmospheric soundingRadio occultationEnvironmental scienceMichelson interferometerSpacecraftRemote sensingAtmospheric sciencesMeteorologyInterferometryPhysicsIonosphereGeologyAstrophysicsOpticsAstronomy

Abstract

fetched live from OpenAlex

Abstract. Nitric oxide (NO) measurements from the Solar Occultation for Ice Experiment (SOFIE) are validated through detailed uncertainty analysis and comparisons with independent observations. SOFIE was compared with coincident satellite measurements from the Atmospheric Chemistry Experiment (ACE) – Fourier Transform Spectrometer (FTS) instrument and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument. The comparisons indicate mean differences of less than ∼50 % for altitudes from roughly 50 to 105 km for SOFIE spacecraft sunrise and 50 to 140 km for SOFIE sunsets. Comparisons of NO time series show a high degree of correlation between SOFIE and both ACE and MIPAS for altitudes below ∼130 km, indicating that measured NO variability in time is robust. SOFIE uncertainties increase below ∼80 km due to interfering H2O absorption and signal correction uncertainties, which are larger for spacecraft sunrise compared to sunset. These errors are sufficiently large in sunrises that reliable NO measurements are infrequent below ∼80 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.039
GPT teacher head0.253
Teacher spread0.213 · 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 designBench or experimental
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

Citations14
Published2019
Admission routes2
Has abstractyes

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