Challenges during Metis-Solar Orbiter commissioning phase
Bibliographic record
Abstract
Metis is the visible light and UV light imaging coronagraph on board the ESA-NASA mission Solar Orbiter that has been launched February 10th, 2020, from Cape Canaveral. Scope of the mission is to study the Sun up close, taking high-resolution images of the Sun’s poles for the first time, and understanding the Sun-Earth connection. Metis coronagraph will image the solar corona in the linearly polarized broadband visible radiation and in the UV HI Ly-α line from 1.6 to 3 solar radii when at Solar Orbiter perihelion, providing a diagnostics, with unprecedented temporal coverage and spatial resolution, of the structures and dynamics of the full corona. Solar Orbiter commissioning phase big challenge was Covid-19 social distancing phase that affected the way commissioning of a spacecraft and its payload is typically done. Metis coronagraph on-board Solar Orbiter had its additional challenges: to wake up and check the performance of the optical, electrical and thermal subsystems, most of them unchecked since Metis delivery to spacecraft prime, Airbus, in May 2017. The roadmap to the fully commissioned coronagraph is here described throughout the steps from the software functional test, the switch on of the detectors of the two channels, UV and visible, to the optimization of the occulting system and the characterization of the instrumental stray light, one of the most challenging features in a coronagraph.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".