Observational constraints on the origin of the elements – VI. Origin and evolution of neutron-capture elements as probed by the <i>Gaia</i>-ESO survey
Bibliographic record
Abstract
ABSTRACT Most heavy elements beyond the iron peak are synthesized via neutron capture processes. The nature of the astrophysical sites of neutron capture processes is still very unclear. In this work, we explore the observational constraints of the chemical abundances of s-process and r-process elements on the sites of neutron-capture processes by applying Galactic chemical evolution (GCE) models to the data from Gaia-ESO large spectroscopic stellar survey. For the r-process, the [Eu/Fe]–[Fe/H] distribution suggests a short delay time of the site that produces Eu. Other independent observations (e.g. NS–NS binaries), however, suggest a significant fraction of long delayed (>1 Gyr) neutron star mergers (NSM). When assuming NSM as the only r-process sites, these two observational constraints are inconsistent at above 1σ level. Including short delayed r-process sites like magnetorotational supernova can resolve this inconsistency. For the s-process, we find a weak metallicity dependence of the [Ba/Y] ratio, which traces the s-process efficiency. Our GCE model with up-to-date yields of AGB stars qualitatively reproduces this metallicity dependence, but the model predicts a much higher [Ba/Y] ratio compared to the data. This mismatch suggests that the s-process efficiency of low-mass AGB stars in the current AGB nucleosynthesis models could be overestimated.
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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".