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Record W4409480440 · doi:10.1029/2025gl115547

Spatial Distribution of Ion Cyclotron Waves at Io

2025· article· en· W4409480440 on OpenAlexafffund
Xing Cao, Shaobei Wang, Binbin Ni, Danny Summers, Yuri Shprits, Peng Lü, Minyi Long

Bibliographic record

VenueGeophysical Research Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsMemorial University of Newfoundland
FundersNational Key Research and Development Program of ChinaChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaTencent
KeywordsCyclotronIonSpatial distributionGeologyPhysicsGeophysicsAtmospheric sciencesRemote sensing

Abstract

fetched live from OpenAlex

Abstract Ion cyclotron waves at Io are important for understanding the complex interactions between Io and Jupiter's magnetosphere. In this study, we analyze the spatial distributions of ion cyclotron waves at Io using data from seven close flybys of Io—five by Galileo and two by Juno. We find that the amplitudes of ion cyclotron waves vary from several nT to ∼100 nT. The averaged wave amplitude reaches its peak at ∼2 RI downstream of Io and diminishes significantly with increasing distance from Io. While ion cyclotron waves are primarily observed downstream of Io, they also occur upstream but with much weaker amplitudes. Notably, these waves are absent within Io's Alfvén wings and plasma wake, likely due to the unique plasma environment in these regions. Our findings shed new light on the distribution properties of ion cyclotron waves at Io, which provide key inputs for exploring the interactions between Io and Jupiter.

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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.283
Teacher spread0.273 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueGeophysical Research Letters→Same topicIonosphere and magnetosphere dynamics→French-language works237,207→