The Radial Velocity Experiment (RAVE): First Data Release
Bibliographic record
Abstract
We present the first data release of the Radial Velocity Experiment (RAVE), an ambitious spectroscopic survey to measure radial velocities and stellar atmosphere parameters (temperature, metallicity, and surface gravity) of up to one million stars using the Six Degree Field multiobject spectrograph on the 1.2 m UK Schmidt Telescope of the Anglo-Australian Observatory. The RAVE program started in 2003, obtaining medium-resolution spectra (median R = 7500) in the Ca-triplet region (8410-8795 Å) for southern hemisphere stars drawn from the Tycho-2 and SuperCOSMOS catalogs, in the magnitude range 9 < I < 12. The first data release is described in this paper and contains radial velocities for 24,748 individual stars (25,274 measurements when including reobservations). Those data were obtained on 67 nights between 2003 April 11 and 2004 April 3. The total sky coverage within this data release is ∼4760 deg 2 . The average signal-to-noise ratio of the observed spectra is 29.5, and 80% of the radial velocities have uncertainties better than 3.4 km s -1 . Combining internal errors and zero-point errors, the mode is found to be 2 km s -1 . Repeat observations are used to assess the stability of our radial velocity solution, resulting in a variance of 2.8 km s -1 . We demonstrate that the radial velocities derived for the first data set do not show any systematic trend with color or signal-to-noise ratio. The RAVE radial velocities are complemented in the data release with proper motions from Starnet 2.0, Tycho-2, and SuperCOSMOS, in addition to photometric data from the major optical and infrared catalogs (Tycho-2, USNO-B, DENIS, and the Two Micron All Sky Survey). The data release can be accessed via the RAVE Web site.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.017 |
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".