Bibliographic record
Abstract
Abstract The velocity shifts of spectral lines as a function of line strength, so-called the third signature of granulation, are investigated using three published solar-flux atlases. We use flux atlases because we wish to treat the Sun as a star, against which stellar observations can be compared and judged. The atlases are critiqued and compared to the lower-resolution observations taken with the Elginfield stellar spectrograph. Third-signature plots are constructed for the 6020–6340 Å region. No dependence on excitation potential or wavelength is found over this wavelength span. The shape of the plots from the three solar atlases is essentially the same, with rms line-core velocity differences of 30–35 m s−1. High-resolution atlas data are degraded to the level of the Elginfield spectrograph and compared to direct observations taken with that spectrograph. The line-core velocities show good agreement, with rms differences of 38 m s−1. A new standard curve is derived and compared with the previously published one. Only small differences in shape are found, but a significant (+97 m s−1) change in the zero point is indicated. The bisector of the Fe i 6253 line is mapped onto the third-signature plots and flux deficits are derived, which measure the granule/lane flux imbalance. The lower spectral resolution lowers the flux deficit area slightly and moves the peak of the deficit 0.3–0.5 km s−1 toward higher velocities. These differences, while significant, are not large compared to measurement errors for stellar data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".