High-velocity Stars in SDSS/APOGEE DR17
Bibliographic record
Abstract
Abstract We report 23 stars having Galactocentric velocities larger than 450 km s−1 in the final data release of the APOGEE survey. This sample was generated using space velocities derived by complementing the high-quality radial velocities from the APOGEE project in Sloan Digital Sky Survey’s Data Release 17 (DR17) with distances and proper motions from Gaia early Data Release 3 (eDR3). We analyze the observed kinematics and derived dynamics of these stars, considering different potential models for the Galaxy. We find that three stars could be unbound depending on the adopted potential, but in general all of the stars show typical kinematics of halo stars. The APOGEE DR17 spectroscopic results and Gaia eDR3 photometry are used to assess the stellar parameters and chemical properties of the stars. All of the stars belong to the red giant branch, and, in general, they follow the abundance pattern of typical halo stars. There are a few exceptions that would deserve further analysis through high-resolution spectroscopy. In particular, we identify a high-velocity Carbon-Enhanced Metal-Poor star, with a Galactocentric velocity of 482 km s−1. We do not confirm any hypervelocity star in the sample, but this result is very sensitive to the adopted distances and less sensitive to the Galactic potential.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".