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Hemispheric and seasonal variations in the cold plasma outflow source region: polar cap ionosphere electron density at 350–500 km

2020· article· en· W3092404145 on OpenAlexaff
Spencer Hatch, S. Haaland, K. M. Laundal, T. Moretto, A. W. Yau, Lindis Merete Bjoland, Jone Peter Reistad, Anders Ohma, Kjellmar Oksavik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSpan (engineering)EndocrinologyBiology

Abstract

fetched live from OpenAlex

The polar cap ionosphere (here defined as the region above 80° magnetic latitude) is the primary source region of cold plasma outflows observed in the magnetosphere. The two factors controlling cold plasma outflows are the availability of plasma in the polar cap ionosphere, and transport from the ionosphere to the magnetosphere. Some statistical studies have indicated that the former of these two factors, availability of cold plasma, is the limiting factor. We use 15 years of electron density measurements made by Swarm and CHAMP spacecraft, corrected for variations in observation altitude and solar activity, to investigate how variations in solar wind driving and local hemispheric season affect the polar cap ionosphere electron density Ne. We show that the dependence of Ne on the By component of the interplanetary magnetic field is apparently antisymmetric in the two hemispheres, that Nestatistically decreases with decreasing Dst index (i.e., increasing geomagnetic activity) and that Ne is apparently insensitive to the AE index. We also show that Ne distributions around March and September equinoxes display weak evidence of hemispheric asymmetry. We show that during local summer, observed Ne distributions under high solar wind driving conditions are relatively lower than Ne distributions under low solar wind driving conditions. During local winter the reverse is true, with Ne distributions under low solar wind driving conditions being relatively lower than Ne distributions under high solar wind driving conditions. Thus solar wind driving and seasonal effects may apparently both constructively and destructively interfere. Altitude variation in Swarm and CHAMP Nemeasurements is accounted for via an empirical scale height derived from 1687 conjunctions between Swarm B and either Swarm A or Swarm C during 2013–2019. The approximately linear dependence of Ne on F10.7 measurements is also accounted for. Swarm Ne measurements are additionally corrected using the Lomidze et al. (2018) calibrations.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.001

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 head0.008
GPT teacher head0.198
Teacher spread0.189 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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