Bibliographic record
Abstract
Eruptive variables are considered to include any variables which flare up relatively quickly, and fade more slowly. They include flare stars which brighten in seconds, and some types of novae and symbiotic stars which may take months or even years to brighten. This class sometimes even includes R Coronae Borealis stars, which are the inverse of eruptive variables! In the GCVS4, this class includes many types of pre-main sequence stars, and also S Doradus, Gamma Cassiopeiae, and erupting Wolf-Rayet stars. In eruptive variables, there is generally a sudden input of energy into a star, or part of a star, and we see the star's response – a violent outburst. Flare stars Flare stars, also known as UV Ceti stars, are dwarf K and M stars (mostly the latter) which randomly and unpredictably increase in brightness within seconds to minutes, by up to several magnitudes, then slowly return to normal (figures 7.1, 7.2). In the GCVS4 they are classified as UV, or UVN if they are associated with pre-main sequence stars, or RS if they occur in an RS Canum Venaticorum binary system. These flares are qualitatively similar to those on the sun. The flares are one aspect of activity on these stars; emission lines in both the visible and ultraviolet spectra, and X-ray emission from a hot (up to 10 000 000 K) corona are others. So flare stars are generally classified as dMe, the ‘e’ referring to the presence of emission lines in the spectrum. Some flare stars are also BY Draconis variables (section 4.5); this is yet another manifestation of their activity.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.028 |
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".