First Results for Solar Soft X-Ray Irradiance Measurements from the Third-generation Miniature X-Ray Solar Spectrometer
Bibliographic record
Abstract
Abstract Three generations of the Miniature X-ray Solar Spectrometer (MinXSS) have flown on small satellites with the goal “to explore the energy distribution of soft X-ray (SXR) emissions from the quiescent Sun, active regions, and during solar flares, and to model the impact on Earth’s ionosphere and thermosphere.” The primary science instrument is the Amptek X123 X-ray spectrometer that has improved with each generation of the MinXSS experiment. This third-generation MinXSS-3 has a higher energy resolution and larger effective area than its predecessors and is also known as the Dual-zone Aperture X-ray Solar Spectrometer (DAXSS). It was launched on the INSPIRESat-1 satellite on 2022 February 14, and INSPIRESat-1 has successfully completed its 6 month prime mission. The INSPIRESat-1 is in a dawn–dusk, Sun-synchronous orbit and therefore has had 24 hr coverage of the Sun during most of its mission so far. The rise of Solar Cycle 25 has been observed by DAXSS. This paper introduces the INSPIRESat-1 DAXSS solar SXR observations, and we focus the science results here on a solar occultation experiment and multiple flares on 2022 April 24. One key flare result is that the reduction of elemental abundances appears greatest during the flare impulsive phase, thus highlighting the important role of chromospheric evaporation during flares to inject warmer plasma into the coronal loops. Furthermore, these results are suggestive that the amount of chromospheric evaporation is related to flare temperature and intensity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".