THE APACHE POINT OBSERVATORY GALACTIC EVOLUTION EXPERIMENT: FIRST DETECTION OF HIGH-VELOCITY MILKY WAY BAR STARS
Bibliographic record
Abstract
Commissioning observations with the Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey III, have produced radial velocities (RVs) for ∼4700 K/M-giant stars in the Milky Way (MW) bulge. These high-resolution ( R ∼ 22, 500), high-S/N (>100 per resolution element), near-infrared (NIR; 1.51–1.70 μm) spectra provide accurate RVs ( V ∼ 0.2 km s −1 ) for the sample of stars in 18 Galactic bulge fields spanning −1° < l < 20°, | b | < 20°, and δ > −32°. This represents the largest NIR high-resolution spectroscopic sample of giant stars ever assembled in this region of the Galaxy. A cold (σ V ∼ 30 km s −1 ), high-velocity peak ( V GSR ≈ +200 km s −1 ) is found to comprise a significant fraction (∼10%) of stars in many of these fields. These high RVs have not been detected in previous MW surveys and are not expected for a simple, circularly rotating disk. Preliminary distance estimates rule out an origin from the background Sagittarius tidal stream or a new stream in the MW disk. Comparison to various Galactic models suggests that these high RVs are best explained by stars in orbits of the Galactic bar potential, although some observational features remain unexplained.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.000 |
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".