Age-resolved chemistry of red giants in the solar neighbourhood
Bibliographic record
Abstract
In the age of high-resolution spectroscopic stellar surveys of the Milky Way, the number of stars with detailed abundances of multiple elements is rapidly increasing. These elemental abundances are directly influenced by the evolutionary history of the Galaxy, but this can be difficult to interpret without an absolute timeline of the abundance enrichment. We present age–abundance trends for [M/H], [α/M], and 17 individual elements using a sample of 721 solar neighbourhood Hipparcos red giant stars observed by Apache Point Observatory Galactic Evolution Experiment. These age trends are determined through a Bayesian hierarchical modelling method presented by Feuillet et al. We confirm that the [α/M]–age relation in the solar neighbourhood is steep and relatively narrow (0.20 dex age dispersion), as are the [O/M]–age and [Mg/M]–age relations. The age trend of [C/N] is steep and smooth, consistent with stellar evolution. The [M/H]–age relation has a mean age dispersion of 0.28 dex and a complex overall structure. The oldest stars in our sample are those with the lowest and highest metallicities, while the youngest stars are those with solar metallicity. These results provide strong constraints on theoretical models of Galactic chemical evolution (GCE). We compare them to the predictions of one-zone GCE models and multizone mixtures, both analytic and numerical. These comparisons support the hypothesis that the solar neighbourhood is composed of stars born at a range of Galactocentric radii, and that the most metal-rich stars likely migrated from a region with earlier and more rapid star formation such as the inner Galaxy.
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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 | 0.000 |
| 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".