Improved distances and ages for stars common to TGAS and RAVE
Bibliographic record
Abstract
We combine parallaxes from the first Gaia data release with the spectrophotometric distance estimation framework for stars in the fifth RAVE survey data release.The combined distance estimates are more accurate than either determination in isolation -uncertainties are on average two times smaller than for RAVE-only distances (three times smaller for dwarfs), and 1.4 times smaller than TGAS parallax uncertainties (two times smaller for giants).We are also able to compare the estimates from spectrophotometry to those from Gaia, and use this to assess the reliability of both catalogues and improve our distance estimates.We find that the distances to the lowest log g stars are, on average, overestimated and caution that they may not be reliable.We also find that it is likely that the Gaia random uncertainties are smaller than the reported values.As a by-product we derive ages for the RAVE stars, many with relative uncertainties less than 20 per cent.These results for 219 566 RAVE sources have been made publicly available, and we encourage their use for studies that combine the radial velocities provided by RAVE with the proper motions provided by Gaia.A sample that we believe to be reliable can be found by taking only the stars with the flag notification 'flag any=0'.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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".