Two groups of red giants with distinct chemical abundances in the bulge globular cluster NGC 6553 through the eyes of APOGEE
Bibliographic record
Abstract
Multiple populations revealed in globular clusters (GCs) are important windows to the formation and evolution of these stellar systems. The metal-rich GCs in the Galactic bulge are an indispensable part of this picture, but the high optical extinction in this region has prevented extensive research. In this work, we use the high-resolution near-infrared (NIR) spectroscopic data from Apache Point Observatory Galactic Evolution Experiment (APOGEE) to study the chemical abundances of NGC 6553, which is one of the most metal-rich bulge GCs. We identify 10 red giants as cluster members using their positions, radial velocities, iron abundances, and NIR photometry. Our sample stars show a mean radial velocity of −0.14 ± 5.47 km s−1, and a mean [Fe/H] of −0.15 ± 0.05. We clearly separate two populations of stars in C and N in this GC for the first time. NGC 6553 is the most metal-rich GC where the multiple stellar population phenomenon is found until now. Substantial chemical variations are also found in Na, O, and Al. However, the two populations show similar Si, Ca, and iron-peak element abundances. Therefore, we infer that the CNO, NeNa, and MgAl cycles have been activated, but the MgAl cycle is too weak to show its effect on Mg. Type Ia and Type II supernovae do not seem to have significantly polluted the second generation stars. Comparing with other GC studies, NGC 6553 shows similar chemical variations as other relatively metal-rich GCs. We also confront current GC formation theories with our results, and suggest possible avenues for improvement in the models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".