New insights on Ba overabundance in open clusters.★ Evidence for the intermediate neutron-capture process at play?
Bibliographic record
Abstract
Recently an increasing number of studies were devoted to measure the abundances of neutron-capture elements heavier than iron in stars belonging to Galactic Open Clusters (OCs). OCs span a sizeable range in metallicity -0.6<[Fe/H]<+0.4), and they show abundances of light elements similar to disk stars of the same age. A different pattern is observed for heavy elements. A large scatter is observed for Ba, with most OCs showing [Ba/Fe] and [Ba/La] overabundant with respect to the Sun. The origin of this overabundance is not clearly understood. With the goal of providing new observational insights we determined radial velocities, atmospheric parameters and chemical composition of 27 giant stars members of five OCs: Cr 110, Cr 261, NGC 2477, NGC 2506 and NGC 5822. We used high-resolution spectra obtained with the UVES spectrograph at ESO Paranal. We perform a detailed spectroscopic analysis of these stars to measure the abundance of up to 22 elements per star. We study the dependence of element abundance on metallicity and age with unprecedented detail, complementing our analysis with data culled from the literature. We confirm the trend of Ba overabundance in OCs, and show its large dispersion for clusters younger than ~4 Gyr. Finally, the implications of our results for stellar nucleosynthesis are discussed. We show in this work that the Ba enrichment compared to other neutron-capture elements in OCs cannot be explained by the contributions from the slow neutron-capture process and the rapid neutron-capture process. Instead, we argue that this anomalous signature can be explained by assuming an additional contribution by the intermediate neutron-capture process.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".