CHEMICAL CARTOGRAPHY WITH APOGEE: METALLICITY DISTRIBUTION FUNCTIONS AND THE CHEMICAL STRUCTURE OF THE MILKY WAY DISK
Bibliographic record
Abstract
Using a sample of 69,919 red giants from the SDSS-III/APOGEE Data Release 12, we measure the distribution of stars in the [ α /Fe] versus [Fe/H] plane and the metallicity distribution functions (MDFs) across an unprecedented volume of the Milky Way disk, with radius 3 < R < 15 kpc and height kpc. Stars in the inner disk ( R < 5 kpc) lie along a single track in [ α /Fe] versus [Fe/H], starting with α -enhanced, metal-poor stars and ending at [ α /Fe] ∼ 0 and [Fe/H] ∼ +0.4. At larger radii we find two distinct sequences in [ α /Fe] versus [Fe/H] space, with a roughly solar- α sequence that spans a decade in metallicity and a high- α sequence that merges with the low- α sequence at super-solar [Fe/H]. The location of the high- α sequence is nearly constant across the disk; however, there are very few high- α stars at R > 11 kpc. The peak of the midplane MDF shifts to lower metallicity at larger R , reflecting the Galactic metallicity gradient. Most strikingly, the shape of the midplane MDF changes systematically with radius, from a negatively skewed distribution at 3 < R < 7 kpc, to a roughly Gaussian distribution at the solar annulus, to a positively skewed shape in the outer Galaxy. For stars with kpc or [ α /Fe] > 0.18, the MDF shows little dependence on R . The positive skewness of the outer-disk MDF may be a signature of radial migration; we show that blurring of stellar populations by orbital eccentricities is not enough to explain the reversal of MDF shape, but a simple model of radial migration can do so.
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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 | 0.003 | 0.002 |
| 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 | 0.001 |
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".