Space weather-related activities and projects on-going at INAF-Turin Observatory
Bibliographic record
Abstract
Abstract The Solar Physics Group at the INAF-Turin Astrophysical Observatory (OATo) is actually involved in different Space Weather (SW) projects and missions. In particular, this Group is currently providing for the ESA SWESNET portal two new data analysis tools aimed at (1) the automated identification of magnetic flux ropes from the in situ data (CME magnetic effectiveness tool) and (2) the automated identification and arrival prediction of CMEs from remote sensing and in situ data (CME propagation and forecast tool). The Group is also developing numerical tools for future applications of interest for SW under the project SWELTO-Space WEather Laboratory in Turin Observatory. Moreover, the Group is participating in two SW missions, and in particular in Helianthus (research and development project on solar photonic propulsion for early SW warnings) and Selene (Solar Exploration by Lunar Eclipsing with Nanosatellites Experiment). In addition to this, the Group is leading or is involved in other “SW enabling science” projects, and in particular the Metis coronagraph on-board ESA Solar Orbiter mission, the ASPIICS coronagraph on-board ESA PROBA-3 mission, and the CorMag coronagraph on-board HEMERA stratospheric balloon. In this framework, the OATo Solar Physics Group is working on fundamental research on “SW enabling science”, dealing with the origin and acceleration of solar wind and Coronal Mass Ejections with remote-sensing data, and their interplanetary propagation and evolution with in situ data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".