Present state and promises to unravel the structure and kinematics of the Milky Way with the RAVE survey
Bibliographic record
Abstract
Abstract The RAdial Velocity Experiment (RAVE) is an ambitious survey to measure the radial velocities, temperatures, surface gravities, metallicities and abundance ratios for up to a million stars using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO), over the period 2003–2011. The survey represents a big advance in our understanding of our own Milky Way galaxy. The main data product will be a southern hemisphere survey of about a million stars. Their selection is based exclusively on their I–band colour, so avoiding any colour-induced bias. RAVE is expected to be the largest spectroscopic survey of the Solar neighbourhood in the coming decade, but with a significant fraction of giant stars reaching out to 10 kpc from the Sun. RAVE offers the first truly representative inventory of stellar radial velocities for all major components of the Galaxy. Here we present the first scientific results of this survey as well as its second data release which doubles the number of previously released radial velocities. For the first time, the release also provides atmospheric parameters for a large fraction of the second year data, making it an unprecedented tool to study the formation of the Milky Way. Plans for further data releases are outlined.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".