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Record W4322007450 · doi:10.5194/egusphere-egu23-9043

Plasma Observatory ESA M7 candidate mission: unveiling plasma energization and energy transport through multiscale observations

2023· preprint· en· W4322007450 on OpenAlexaff
M. F. Marcucci, Alessandro Retinò, M. W. Dunlop, C. Forsyth, Y. V. Khotyaintsev, O. Le Contel, I. R. Mann, R. Nakamura, Minna Palmroth, Ferdinand Plaschke, J. Souček, M. Yamauchi, A. Vaivads, F. Valentini

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Environment Research CouncilSight Research UK
KeywordsPhysicsPlasmaMagnetic reconnectionSolar windAstrophysical plasmaSpace physicsSpace weatherKinetic energyObservatoryEnergy transportGeophysicsComputational physicsAstrophysicsClassical mechanicsEngineering physics

Abstract

fetched live from OpenAlex

The Earth's Magnetospheric System is the complex and highly dynamic environment in near-Earth space where plasma gets actively energized and transport of large amounts of energy occurs, due to the interaction of the solar wind with the Earth's magnetic field. Understanding plasma energization and energy transport is an open challenge of space plasma physics, with important implications for space weather science as well as for the understanding of distant astrophysical plasmas. Plasma energization and energy transport are related to fundamental processes such as shocks, magnetic reconnection, turbulence and waves, plasma jets and instabilities, which are at the core of the current space plasma physics research. ESA/Cluster and NASA/MMS four-point constellations, as well as the large-scale multipoint mission NASA/THEMIS, have greatly improved over the last two decades our understanding of plasma processes at individual scales compared to earlier single-point measurements. Despite the large amount of available observations, we still do not fully understand the physical mechanisms which give rise to plasma energization and energy transport. The reason is that the fundamental physical processes governing plasma energization and energy transport operate across multiple scales ranging from the large fluid to the smaller kinetic scales. Here we present the Plasma Observatory (PO) multiscale mission concept which is tailored to study plasma energization and energy transport within the Earth's Magnetospheric System. PO baseline is comprised of one mothercraft (MSC) and six identical smallsat daughtercraft (DSC) in an HEO 8 RE X 18 RE orbit, covering all the key regions of the Magnetospheric System where strong energization and transport occur: the foreshock, bow shock, magnetosheath, magnetopause, magnetotail current sheet, and the transition region. MSC payload provides a complete characterization of electromagnetic fields and plasma particles in a single point with time resolution sufficient to resolve kinetic physics at sub-ion scales. The DSCs have identical payload which is much simpler than on the MSC, yet giving a full characterization of the plasma at the ion and fluid scales. Going beyond Cluster, THEMIS and MMS, PO will permit us to resolve for the first time the coupling between ion and fluid scales as well as the non-planarity and non-stationarity of plasma structures at those scales. PO is one of the five ESA M7 candidates to be launched around 2037 and is currently undergoing a competitive Phase 0 at ESA for further downselection to Phase A at the end of 2023.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.029
GPT teacher head0.243
Teacher spread0.214 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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