From the bulge to the outer disc:
Bibliographic record
Abstract
We combine high-resolution spectroscopic data from APOGEE-2 survey Data Release 16 (DR16) with broad-band photometric data from several sources as well as parallaxes from Gaia Data Release 2 (DR2). Using the Bayesian isochrone-fitting code StarHorse, we derived the distances, extinctions, and astrophysical parameters for around 388 815 APOGEE stars. We achieve typical distance uncertainties of ∼6% for APOGEE giants, ∼2% for APOGEE dwarfs, and extinction uncertainties of ∼0.07 mag, when all photometric information is available, and ∼0.17 mag if optical photometry is missing. StarHorse uncertainties vary with the input spectroscopic catalogue, available photometry, and parallax uncertainties. To illustrate the impact of our results, we show that thanks to Gaia DR2 and the now larger sky coverage of APOGEE-2 (including APOGEE-South), we obtain an extended map of the Galactic plane. We thereby provide an unprecedented coverage of the disc close to the Galactic mid-plane (|ZGal| < 1 kpc) from the Galactic centre out to RGal ∼ 20 kpc. The improvements in statistics as well as distance and extinction uncertainties unveil the presence of the bar in stellar density and the striking chemical duality in the innermost regions of the disc, which now clearly extend to the inner bulge. We complement this paper with distances and extinctions for stars in other public released spectroscopic surveys: 324 999 in GALAH DR2, 4 928 715 in LAMOST DR5, 408 894 in RAVE DR6, and 6095 in GES DR3.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".