Bibliographic record
Abstract
Abstract Convection occurs in the visible photospheric layers of most stars having Te less than about 10000 K, and in some hotter stars. The solar granulation pattern is a symptom of this, as is the non-zero microturbulent velocity often required in abundance analysis to make both weak and strong lines yield the same abundance. In very sharp-lined stars, the presence of a non-thermal velocity field in the visible stellar atmosphere leads to several other effects which may be detected in spectral line profiles. These include radial velocities that vary systematically with equivalent width, distortions of the line profile as compared to a profile computed with a Voigt profile and rotational broadening (“macroturbulence”), and asymmetries with respect to the line centre (“bisector curvature”). Detection and interpretation of these effects, with the goal of obtaining empirical information about a velocity field present in the visible layers, requires comparison with calculated synthetic spectra which incorporate model velocity fields. Thus, this review will summarize some of the observational clues concerning photospheric velocity fields, as well as modelling aimed at interpreting these 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".