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Record W7074632743

North-south asymmetry of the high-latitude thermospheric density: IMF BY effect

2015· article· en· W7074632743 on OpenAlexfundno aff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
FundersUniversität BremenU.S. Geological SurveyFlorida Institute of TechnologyNatural Environment Research CouncilAlberta Agricultural Research InstituteNational Aeronautics and Space Administration
KeywordsAsymmetryEarth's magnetic fieldInterplanetary magnetic fieldNorthern HemisphereSouthern HemisphereThermosphereSatelliteConvection
DOInot available

Abstract

fetched live from OpenAlex

Previous studies have established that the y component of the interplanetary magnetic field (IMF By) plays a role in the north-south asymmetry of the high-latitude plasma convection and wind. The effect of the positive/negative IMF By in the Northern Hemisphere resembles the effect that the negative/positive IMF By would have in the Southern Hemisphere. In this study, we demonstrate that the IMF By effect can also contribute to the hemispheric asymmetry of the thermospheric density. We use high-accuracy air drag measurements from the CHAllenging Minisatellite Payload (CHAMP) satellite and SuperMAG AE index during the period 2001–2006 to examine the response of the high-latitude thermospheric density to geomagnetic activity. Our statistical analysis reveals that the density response at 400 km is greater in the Southern Hemisphere under positive IMF By conditions, and greater in the Northern Hemisphere under negative IMF By conditions. The results suggest that the IMF By effect needs to be taken into account in upper atmospheric modeling for an accurate description of high-latitude densities during periods of enhanced geomagnetic activity.

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)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.159
Teacher spread0.139 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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