Cosmic variance in [O/Fe] in the Galactic disk
Bibliographic record
Abstract
We examine the distribution of the [O/Fe] abundance ratio in stars across the Galactic disk using H-band spectra from the Apache Point Galactic Evolution Experiment (APOGEE). We minimize systematic errors by considering groups of stars with similar atmospheric parameters. The APOGEE measurements in the Sloan Digital Sky Survey data release 12 reveal that the square root of the star-to-star cosmic variance in the oxygen-to-iron ratio at a given metallicity is about 0.03–0.04 dex in both the thin and thick disk. This is about twice as high as the spread found for solar twins in the immediate solar neighborhood and the difference is probably associated to the wider range of galactocentric distances spanned by APOGEE stars. We quantify the uncertainties by examining the spread among stars with the same parameters in clusters; these errors are a function of effective temperature and metallicity, ranging between 0.005 dex at 4000 K and solar metallicity, to about 0.03 dex at 4500 K and [Fe/H] ≃ −0.6. We argue that measuring the spread in [O/Fe] and other abundance ratios provides strong constraints for models of Galactic chemical evolution.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".