Bibliographic record
Abstract
These are the memoirs of fifty years of research in solar physics, closely related to the history of three of the major solar space missions, from the Solar Maximum Mission, SMM, to Solar Orbiter, at present in navigation toward vantage points closer and closer to the Sun. My interest in solar physics was stimulated by the studies on cosmic rays at the University of Turin, and the research in this field initiated at Stanford University as a postdoctoral fellow in the team of John Wilcox with studies on the large-scale corona and its rotation. Thanks to Alan Gabriel, during my first space mission, SMM, I was involved in the operations and scientific data analysis of the Soft X-ray Polychromator. Together with Giancarlo Noci and Giuseppe Tondello, I participated in the realization of the UltraViolet Coronagraph Spectrometer, NASA/ASI, flown on-board SOHO. After this experience there was the opportunity to participate in the formulation of the proposal of the Solar Orbiter mission, and to guide the team, which for this mission developed the Metis coronagraph, up to the delivery of the instrument to the European Space Agency in 2017.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".