The Apache Point Observatory extra-Galactic Evolution Experiment (APOeGEE): Chemical Abundance Trends for Seven Dwarf Spheroidal Galaxies in the APOGEE Survey
Bibliographic record
Abstract
In addition to comprehensive surveys of the Milky Way bulge, disk, and halo, the Apache Point Galactic Evolution Experiment (APOGEE) project observed seven dwarf spheroidal satellites (dSphs) of the Milky Way: Carina, Sextans, Sculptor, Draco, Ursa Minor, Bootes 1, and Fornax. APOGEE radial velocities, stellar parameters, and Gaia EDR3 proper motions are used to identify member stars in the vicinity of each dwarf. To properly analyze the abundance patterns of these galaxies, a novel procedure was developed to determine the measurable upper limits of the APOGEE chemical abundances as a function of the effective temperature and the spectral signal-to-noise ratio. In general, the APOGEE abundance patterns of these galaxies (limited to [Fe/H] $>$ -2.5) agree with those found in high-resolution optical studies after abundance offsets are applied. Most of the galaxies studied have abundance patterns that are distinctly different from the majority of stars found in the MW halo, suggesting that these galaxies contributed little to the MW halo above [Fe/H] $>$ -2.0. From these abundance patterns, we find that these dSphs tend to follow two types of chemical evolution paths: episodic and continuous star formation, a result that is consistent with previous photometric studies of their star formation histories. We explore whether mass and/or environment have an impact on whether a galaxy has an episodic or continuous star formation history, finding evidence that, in addition to the galaxy's mass, proximity to a larger galaxy and the cessation of star formation may drive the overall shape of the 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".