A Galactic Self-portrait: Density Structure and Integrated Properties of the Milky Way Disk
Bibliographic record
Abstract
Abstract The evolutionary history of the Milky Way disk is imprinted in the ages, positions, and chemical compositions of individual stars. In this study, we derive the intrinsic density distribution of different stellar populations using the final data release of the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey. A total of 203,197 red giant branch stars are used to sort the stellar disk (R ≤ 20 kpc) into subpopulations of metallicity (Δ[M/H] = 0.1 dex), age ( Δ log ( age yr ) = 0.1 ), and α-element abundances ([α/M]). We fit the present-day structural parameters and density distribution of each stellar subpopulation after correcting for the survey selection function. The low-α disk is characterized by longer scale lengths and shorter scale heights, and is best fit by a broken exponential radial profile for each population. The high-α disk is characterized by shorter scale lengths and larger scale heights, and is generally well-approximated by a single exponential radial profile. These results are applied to produce new estimates of the integrated properties of the Milky Way from early times to the present day. We measure the total stellar mass of the disk to be 5.2 7 − 1.5 + 0.2 × 1 0 10 M ⊙, and the average mass-weighted scale length is R d = 2.37 ± 0.2 kpc. The Milky Way’s present-day color of (g − r) = 0.72 ± 0.02 is consistent with the classification of a red spiral galaxy, although it has only been in the “green valley” region of the galaxy color–mass diagram for the last ∼3 Gyr.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".