The double sub-giant branch of NGC 6656 (M 22): a chemical characterization
Bibliographic record
Abstract
We present an abundance analysis of 101 subgiant branch (SGB) stars in the globular cluster M 22. Using low-resolution FLAMES/GIRAFFE spectra we have determined abundances of the neutron-capture strontium and barium and the light element carbon. With these data we explore relationships between the observed SGB photometric split in this cluster and two stellar groups characterized by different contents of iron, slow neutron-capture process (s-process) elements, and the α element calcium, which we previously discovered in M 22’s red-giant stars. We show that the SGB stars correlate in chemical composition and the color–magnitude diagram position. The stars with higher metallicity and relative s-process abundances define a fainter SGB, while stars with lower metallicity and s-process content reside on a relatively brighter SGB. This result has implications for the relative ages of the two stellar groups of M 22. In particular, it is inconsistent with a broad spread in ages of the two SGBs. By accounting for the chemical content of the two stellar groups, isochrone fitting of the double SGB suggests that their agesare not different by more than ~300 Myr.
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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 | 0.001 |
| 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".