In-flight radiometric calibration of the Metis Visible Light channel using stars and comparison with STEREO-A/COR2 data
Bibliographic record
Abstract
Context.We present the results for the in-flight radiometric calibration performed for the Visible Light (VL) channel of the Metis coronagraph on board Solar Orbiter. Aims.The radiometric calibration is a fundamental step in building the official pipeline of the instrument, devoted to producing the calibrated data in physical units (L2 data). Methods.To obtain the radiometric calibration factor (ϵVL), we used stellar targets transiting the Metis field of view. We derivedϵVLby determining the signal of each calibration star by means of the aperture photometry and calculating its expected flux in the Metis band pass. The analyzed data set covers the time range from the beginning of the Cruise Phase of the mission (June 2020) until March 2021. Results.Considering the uncertainties, the estimated factorϵVLis in a good agreement with that obtained during the on-ground calibration campaign. This implies that up to March 2021 there was no measurable reduction in the VL channel throughput. Finally, we compared the total and polarized brightness visible light images of the solar corona acquired with Metis and STEREO-A/COR2 during the November 2020 superior conjunction of these instruments. A general good agreement was obtained between the images of these instruments for both the total and polarized brightness.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".