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Record W4392580375 · doi:10.5194/egusphere-egu24-10862

Improving the REleASE solar proton forecasting capabilities with evidence of particle escape from the Sun: HESPERIA REleASE + 

2024· preprint· en· W4392580375 on OpenAlexaboutno aff
O. Malandraki, A. Posner, Michalis Karavolos, K. Tziotziou, Fanis Smanis, Monica Laurenza, Janet Barzilla, E. Semones, Kathryn Whitman, M. L. Mays, Chinwe Didigu, Christopher J. Stubenrauch, B. Heber, Patrick Kuehl, M. Maksimović, Vratislav Krupař, Nikolas Milas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSunlightParticle (ecology)ProtonAstrobiologyEnvironmental sciencePhysicsAstronomyGeologyOceanographyNuclear physics

Abstract

fetched live from OpenAlex

Providing reliable forecasts of Solar Energetic Particle (SEP) events is mandatory for human spaceflight beyond low-Earth orbit, especially outside the Earth's magnetosphere. High-energy SEPs are tracked because they penetrate deeper into the terrestrial atmosphere and contribute to the radiation dose aboard spacecraft specifically over Canada and the Southern Indian Ocean, due to the tilt of the Earth on its axis. Based on the Relativistic Electron Alert System for Exploration (REleASE) forecasting scheme], the HESPERIA REleASE product was developed by the HESPERIA H2020 project (Project Coordinator: Dr. Olga Malandraki) and generating real-time predictions of the proton flux (30-50 MeV) at L1, making use of relativistic and near-relativistic electron measurements by the SOHO/EPHIN and ACE/EPAM experiments, respectively. The HESPERIA REleASE tools are operational through the Space Weather Operational Unit of the National Observatory of Athens, accessible through the dedicated website (http://www.hesperia.astro.noa.gr). HESPERIA REleASE has attracted attention from various space organizations (e.g., NASA/CCMC, SRAG), due to the real-time, highly accurate and timely performance offered. ESA selected the HESPERIA REleASE products that were integrated and provided through the ESA Space Weather (SWE) Service Network (https://swe.ssa.esa.int/noa-hesperia-federated) under the Space Radiation Expert Service Center (R-ESC). Solar cycle 25 solar radiation storms successfully predicted by HESPERIA REleASE are presented and discussed. Moreover, we present an innovative upgrade implemented, namely HESPERIA REleASE+, that is using the novel approach of combining for the first time real-time type III solar radio burst observations by the STEREO S/WAVES instrument, thus incorporating clear evidence of particle escape from the Sun, within the HESPERIA REleASE system. To this end, a robust automated algorithm has been developed for the real-time identification and classification of Type III radio burst characteristics, related to intense SEP events at Earth’s orbit. This new implementation leads to a substantial step forward in improving the accuracy and reduction of false alarms.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.014

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 head0.030
GPT teacher head0.249
Teacher spread0.218 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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