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Record W4408442117 · doi:10.5194/egusphere-egu25-3168

Foreshock transient impact on the magnetosheath, magnetosphere and ionosphere

2025· preprint· en· W4408442117 on OpenAlexaboutno aff
Hyangpyo Kim, R. Nakamura, Jaeheung Park, Adriana Settino, Kyoung‐Joo Hwang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetosheathForeshockMagnetosphereIonosphereGeophysicsTransient (computer programming)PhysicsGeologyMagnetopausePlasmaSeismologyComputer science

Abstract

fetched live from OpenAlex

We present multi-scale observations of a foreshock transient and its impact on the magnetosheath, magnetosphere and ionosphere, utilizing the data from Cluster, THEMIS, ground-based radars, and magnetometers. During the storm recovery phase on March 25, 2015, the Cluster spacecraft observed the foreshock transient at GSE (8, -0.5, -13) Re. Subsequently, THEMIS A and E, residing in the equatorial plane, detected large-scale high-speed jets in the postnoon sector between 7 and 9 Re from Earth. At geosynchronous orbit, GOES-13 crossed the magnetopause, during which strong poleward plasma convection and tongue of ionization (TOI) were detected by incoherent scatter radars at Prince George, Saskatoon, Kapuskasing, and Rankin Inlet stations and GPS total electron content (TEC) measurements. The signature of field-aligned currents was observed by ground magnetometers. These simultaneous observations indicate that the foreshock transient plays an important role in energy transfer between the solar wind, the magnetosphere, and the ionosphere. This event provides the first observational evidence that a foreshock transient can lead to significant disturbances in the coupled magnetosphere-ionosphere system, being an important ingredient in space weather.

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 score0.011
Threshold uncertainty score0.023

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)0.0010.000

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 head0.011
GPT teacher head0.224
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 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
Published2025
Admission routes1
Has abstractyes

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