MétaCan
Menu
Back to cohort
Record W2158271911 · doi:10.1186/bf03352904

Analyzing the variation of embedding dimension of solar and geomagnetic activity indices during geomagnetic storm time

2009· article· en· W2158271911 on OpenAlexaboutno aff
Masoud Mirmomeni, C. Lucas

Bibliographic record

VenueEarth Planets and Space · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGeomagnetic stormAttractorSpace weatherCoronal mass ejectionEarth's magnetic fieldChaoticMeteorologyEnvironmental scienceStormGeophysicsGeologyPhysicsSolar windComputer scienceMathematicsMathematical analysisArtificial intelligenceMagnetic field

Abstract

fetched live from OpenAlex

Abstract Cyclic solar activity as one of the natural chaotic phenomena has significant effects on Earth, climate, and satellites. Rapid changes in the near-Earth space environment can affect the performance and reliability of both spacecraft and ground-based systems. This can imply major problems due to communication and satellite operational anomalies. Therefore, it is meaningful to analyze solar activity and geomagnetic indices to elicit the behavior of sun as the origin of most of these chaotic phenomena. One of the most important tools for analyzing the chaotic trends is the “Embedding Dimension” (ED). In this paper, the variation of ED for solar activity indices especially during storm time for two well-known storms is considered. The first storm is the super-storm on 13 March 1989, which shuts down the power supply system in Québec, Canada and the second one is the storm caused by Coronal Mass Ejection on 11 January 1997 which causes the failure of Telstar 401 satellite. The method of this paper is based on the fact that the reconstructed dynamics of an attractor should be a smooth map, i.e. with no self intersection in the reconstructed attractor. It is shown that the Embedding Dimension (and other chaotic characteristics) of some solar and geomagnetic activity indices during these storms varies rapidly.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.381
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.003
GPT teacher head0.195
Teacher spread0.192 · 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 teacher head, 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

Citations9
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueEarth Planets and SpaceSame topicSolar and Space Plasma DynamicsFrench-language works237,207