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Record W4378831391 · doi:10.1029/2023gl102758

What Is the Altitude of Thermal Equilibrium?

2023· article· en· W4378831391 on OpenAlexafffund
W. K. Peterson, Naomi Maruyama, P. G. Richards, P. J. Erickson, A. B. Christensen, A. W. Yau

Bibliographic record

VenueGeophysical Research Letters · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersNational Aeronautics and Space AdministrationCanadian Space AgencyNational Science Foundation
KeywordsThermosphereAltitude (triangle)IonosphereAtmospheric sciencesPhysicsIncoherent scatterThermalisationAtmosphere (unit)ExosphereThermalElectron temperatureIonAtmospheric modelsComputational physicsElectronEnvironmental scienceGeophysicsAtomic physicsMeteorologyNuclear physics

Abstract

fetched live from OpenAlex

Abstract Thermal equilibrium in planetary atmospheres occurs at altitudes where the ion, electron, and neutral temperatures are equal. Thermal equilibrium is postulated to occur in the collision‐dominated ionosphere. This postulated altitude is above the lower boundary of all empirical models of planetary ionospheres. Physics‐based model predictions of the altitude cannot be validated due to a lack of adequate simultaneous observations of temperature profiles. This study presents temperature profiles from simultaneous observations on Atmosphere Explorer–C below 140 km and quiet‐time neutral observations from Thermosphere Ionosphere Mesosphere Energy and Dynamics/Global UltraViolet Imager over Millstone Hill. These are compared with profiles from physics‐based models with a discussion of their respective limitations. We conclude that there does not yet exist a quantitative understanding of the ion, electron, and neutral thermalization processes in low‐altitude planetary ionospheres. Progress on this topic requires an adequate database of simultaneous ion, electron, and neutral temperature profiles in the 110–140 km altitude range.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

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