The Sixth Data Release of the Radial Velocity Experiment (RAVE). I. Survey Description, Spectra, and Radial Velocities
Bibliographic record
Abstract
Abstract The Radial Velocity Experiment (R ave ) is a magnitude-limited (9 < I < 12) spectroscopic survey of Galactic stars randomly selected in Earth’s southern hemisphere. The R ave medium-resolution spectra ( R ∼ 7500) cover the Ca-triplet region (8410–8795 Å). The sixth and final data release (DR6) is based on 518,387 observations of 451,783 unique stars. R ave observations were taken between 2003 April 12 and 2013 April 4. Here we present the genesis, setup, and data reduction of R ave as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in R ave DR6. Furthermore, we present derived spectral classification and radial velocities for the R ave targets, complemented by cross-matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch, and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km s –1 , while 95% of the objects have radial velocities better than 4.0 km s –1 . Stellar atmospheric parameters, abundances and distances are presented in a subsequent publication. The data can be accessed via the R ave website ( http://rave-survey.org ) or the Vizier database.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.029 |
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".