CHROMOSPHERICALLY ACTIVE STARS IN THE RADIAL VELOCITY EXPERIMENT (RAVE) SURVEY. I. THE CATALOG
Bibliographic record
Abstract
RAVE, the unbiased magnitude limited survey of southern sky stars, contained 456,676 medium-resolution spectra at the time of our analysis. Spectra cover the Ca ii infrared triplet (IRT) range, which is a known indicator of chromospheric activity. Our previous work classified all spectra using locally linear embedding. It identified 53,347 cases with a suggested emission component in calcium lines. Here, we use a spectral subtraction technique to measure the properties of this emission. Synthetic templates are replaced by the observed spectra of non-active stars to bypass the difficult computations of non-local thermal equilibrium profiles of the line cores and stellar parameter dependence. We derive both the equivalent width of the excess emission for each calcium line on a 5 Å wide interval and their sum EW IRT for ∼44,000 candidate active dwarf stars with signal-to-noise ratio >20, with no cuts on the basis of the source of their emission flux. From these, ∼14,000 show a detectable chromospheric flux with at least a 2σ confidence level. Our set of active stars vastly enlarges previously known samples. Atmospheric parameters and, in some cases, radial velocities of active stars derived from automatic pipelines suffer from systematic shifts due to their shallower calcium lines. We re-estimate the effective temperature, metallicity, and radial velocities for candidate active stars. The overall distribution of activity levels shows a bimodal shape, with the first peak coinciding with non-active stars and the second with the pre-main-sequence cases. The catalog will be made publicly available with the next RAVE public data releases.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".