Mapping the solar wind HI outflow velocity in the inner heliosphere by coronagraphic ultraviolet and visible-light observations
Bibliographic record
Abstract
We investigated the capability of mapping the solar wind outflow velocity of neutral hydrogen atoms by using synergistic visible-light and ultraviolet observations. We used polarised brightness images acquired by the LASCO/SOHO and Mk3/MLSO coronagraphs, and synoptic Lyα line observations of the UVCS/SOHO spectrometer to obtain daily maps of solar wind H I outflow velocity between 1.5 and 4.0 R⊙ on the SOHO plane of the sky during a complete solar rotation (from 1997 June 1 to 1997 June 28). The 28-days data sequence allows us to construct coronal off-limb Carrington maps of the resulting velocities at different heliocentric distances to investigate the space and time evolution of the outflowing solar plasma. In addition, we performed a parameter space exploration in order to study the dependence of the derived outflow velocities on the physical quantities characterising the Lyα emitting process in the corona. Our results are important in anticipation of the future science with the Metis instrument, selected to be part of the Solar Orbiter scientific payload. It was conceived to carry out near-sun coronagraphy, performing for the first time simultaneous imaging in polarised visible-light and ultraviolet H I Lyα line, so providing an unprecedented view of the solar wind acceleration region in the inner corona.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".