A2A: 21 000 bulge stars from the ARGOS survey with stellar parameters on the APOGEE scale
Bibliographic record
Abstract
Aims. Spectroscopic surveys have by now collectively observed tens of thousands of stars in the bulge of our Galaxy. However, each of these surveys had unique observing and data processing strategies that led to distinct stellar parameter and abundance scales. Because of this, stellar samples from different surveys cannot be directly combined. Methods. Here we use the data-driven method, The Cannon , to bring 21 000 stars from the ARGOS bulge survey, including 10 000 red clump stars, onto the parameter and abundance scales of the cross-Galactic survey, APOGEE , obtaining rms precisions of 0.10 dex, 0.07 dex, 74 K, and 0.18 dex for [Fe/H], [Mg/Fe], T eff , and log( g ), respectively. The re-calibrated ARGOS survey – which we refer to as the A2A survey – is combined with the APOGEE survey to investigate the abundance structure of the Galactic bulge. Results. We find X-shaped [Fe/H] and [Mg/Fe] distributions in the bulge that are more pinched than the bulge density, a signature of its disk origin. The mean abundance along the major axis of the bar varies such that the stars are more [Fe/H]-poor and [Mg/Fe]-rich near the Galactic centre than in the outer bulge and the long bar region. The vertical [Fe/H] and [Mg/Fe] gradients vary between the inner bulge and the long bar, with the inner bulge showing a flattening near the plane that is absent in the long bar. The [Fe/H] − [Mg/Fe] distribution shows two main maxima, an ‘[Fe/H]-poor [Mg/Fe]- rich’ maximum and an ‘[Fe/H]-rich [Mg/Fe]-poor’ maximum, that vary in strength with position in the bulge. In particular, the outer long bar close to the Galactic plane is dominated by super-solar [Fe/H], [Mg/Fe]-normal stars. Stars composing the [Fe/H]-rich maximum show little kinematic dependence on [Fe/H], but for lower [Fe/H] the rotation and dispersion of the bulge increase slowly. Stars with [Fe/H] < −1 dex have a very different kinematic structure than stars with higher [Fe/H]. Conclusions. Comparing with recent models for the Galactic boxy-peanut bulge, the abundance gradients and distribution, and the relation between [Fe/H] and kinematics suggests that the stars comprising each maximum have separate disk origins with the ‘[Fe/H]-poor [Mg/Fe]-rich’ stars originating from a thicker disk than the ‘[Fe/H]-rich [Mg/Fe]-poor’ stars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 0.003 |
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".