Distance determination for RAVE stars using stellar models
Bibliographic record
Abstract
We apply the method of Burnett & Binney (2010, MNRAS, 407, 339) for the determination of stellar distances and parameters to the internal catalogue of the RAdial Velocity Experiment (RAVE; Steinmetz et al. 2006, AJ, 132, 1645). Subsamples of stars that either have Hipparcos parallaxes or belong to well-studied clusters inspire confidence in the formal errors. Distances to dwarfs cooler than ~6000 K appear to be unbiased, but those to hotter dwarfs tend to be too small by ~10% of the formal errors. Distances to giants tend to be too large by about the same amount. The median distance error in the whole sample of 216 000 stars is 28% and the error distribution is similar for both giants and dwarfs. Roughly half the stars in the RAVE survey are giants. The giant fraction is largest at low latitudes and in directions towards the Galactic Centre. Near the plane the metallicity distribution is remarkably narrow and centred on [M/H] = −0.04 dex; with increasing |z| it broadens out and its median moves to [M/H] ≃ −0.5. Mean age as a function of distance from the Galactic centre and distance |z| from the Galactic plane shows the anticipated increase in mean age with |z|.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".