Chemical Abundances in the Ultra-faint Dwarf Galaxies Grus I and Triangulum II: Neutron-capture Elements as a Defining Feature of the Faintest Dwarfs*
Bibliographic record
Abstract
Abstract We present high-resolution spectroscopy of four stars in two candidate ultra-faint dwarf galaxies (UFDs), Grus I (Gru I) and Triangulum II (Tri II). Neither object currently has a clearly determined velocity dispersion, placing them in an ambiguous region of parameter space between dwarf galaxies and globular clusters (GCs). No significant metallicity difference is found for the two Gru I stars, but both stars are deficient in neutron-capture elements. We verify previous results that Tri II displays significant spreads in metallicity and [α/Fe]. Neutron-capture elements are not detected in our Tri II data, but we place upper limits at the lower envelope of Galactic halo stars, consistent with previous very low detections. Stars with similarly low neutron-capture element abundances are common in UFDs but rare in other environments. This signature of low neutron-capture element abundances traces chemical enrichment in the least massive star-forming dark matter halos and further shows that the dominant sources of neutron-capture elements in metal-poor stars are rare. In contrast, all known GCs have similar ratios of neutron-capture elements to those of halo stars, suggesting that GCs do not form at the centers of their own dark matter halos. The low neutron-capture element abundances may be the strongest evidence that Gru I and Tri II are (or once were) galaxies rather than GCs, and we expect future observations of these systems to robustly find nonzero velocity dispersions or signs of tidal disruption. However, the nucleosynthetic origin of this low neutron-capture element floor remains unknown.
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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 | 0.000 |
| 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 | 0.001 | 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".