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Record W4322004786 · doi:10.5194/egusphere-egu23-9081

A cross-discipline approach to examine the physical links between Weather in Space and the Lower Atmosphere

2023· preprint· en· W4322004786 on OpenAlexaff
M. G. G. T. Taylor, Rune Floberghagen, A. Strømme, M. Rast, Lisa Baddeley, Michel Blanc, E. Donovan, Eelco Doornbos, Roger Haagmans, Kirsti Kauristie, L. Kepko, S. E. Milan, H. J. Opgenoorth, Noora Partamies, Tim Stockdale, Claudia Stolle

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAtmosphere (unit)Agency (philosophy)Space weatherSpace (punctuation)IonosphereWork (physics)Political scienceEnvironmental scienceMeteorologyComputer scienceGeographyGeophysicsSociologyEngineeringPhysicsSocial scienceMechanical engineering

Abstract

fetched live from OpenAlex

Earth’s atmosphere provides the background for the “sea of plasmas” surrounding Earth via its Ionosphere and the upper and middle Atmosphere, providing an interface layer through which a broad diversity of solar-terrestrial energy transfer processes takes place. Developing an integrative understanding of global geospace energy transfer processes affecting this layer is a major scientific challenge with important societal implications. The disciplines covering this interaction have a large, diverse and active international community, with significant expertise and heritage in the European Space Agency and Europe. Several ESA directorates have activities directly connected with this topic, and an ESA Heliophysics Working group has been appointed by several ESA Directors, under the direction of the ESA Director General, to work on optimizing synergies and to act as a focus for discussion, inside ESA, of the scientific interests of the Heliophysics community.Very recently, a Forum at the International Space Science Institute was set up, involving some of the above WG, to look towards developing a deeper understanding of the solar-terrestrial interactions between the Ionosphere and the upper- and middle atmosphere, thus possibly enabling the detection of signatures by natural and anthropogenic hazards.This presentation will provide a brief introduction to ongoing internal ESA cross discipline approaches, and then note some of the outcomes of this recent ISSI forum to set out a pathway to address this intriguing topic.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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