Bibliographic record
Abstract
Major outstanding problems in solar physics relate to solar magnetism. Spectropolarimetry offers the best, and sometimes only, method of obtaining accurate measurements of the Sun’s magnetic field. New 1.5–2 m class telescopes with adaptive optics have come on line, and the Daniel K. Inouye 4 m Solar Telescope (DKIST) will begin observing in 2019. The calibration of polarized light entering such a large and polarizing ground-based telescope represents difficult challenges. This paper explores how special polarization properties of particular atomic transitions may provide calibration data, augmenting or even avoiding time-consuming calibration observations, as well as science data. This initial study concludes that solar spectral lines exist with special polarization properties, allowing the telescope calibration to be determined. The Sun’s visible and infrared spectrum is dominated by lines of neutral atoms and singly charged ions of iron and other complex atoms. Both solar and atomic physics should jointly benefit from telescopic advances, as observers explore regimes of broader wavelength ranges, and higher spatial resolutions and polarimetric sensitivities, than they have reached in the past. Further work is in progress to identify particular transitions of practical use to aid in calibrations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".