Evidence for multiple nucleosynthetic processes from carbon-enhanced metal-poor stars in the Carina dwarf spheroidal galaxy
Bibliographic record
Abstract
Context.Carbon-enhanced metal-poor (CEMP) stars ([C/Fe] > 0.7) are known to exist in large numbers at low metallicity in the Milky Way halo and are important tracers of early Galactic chemical evolution. However, very few stars of this kind have been identified in the classical dwarf spheroidal (dSph) galaxies, and detailed abundances, including neutron-capture element abundances, have only been reported for 13 stars. Aims.We aim to derive detailed abundances of six CEMP stars identified in the Carina dSph and compare the abundances to CEMP stars in other dSph galaxies and the Milky Way halo. This is the largest sample of CEMP stars in a dSph galaxy analysed to date. Methods.One-dimensional local thermodynamic equilibrium (LTE) elemental abundances are derived via equivalent width and spectral synthesis using high-resolution spectra of the six stars obtained with the MIKE spectrograph at Las Campanas Observatory. Results.We derived abundances or upper limits for up to 27 elements from C to Os in the six stars. Our analysis reveals one of the stars to be a CEMP-no star with very low neutron-capture element abundances. In contrast, the other five stars all show enhancements in neutron-capture elements in addition to their carbon enhancement, classifying them as CEMP-sand -r/sstars. The six stars have similarαand iron-peak element abundances to other stars in Carina, except for the CEMP-no star, which shows enhancement in Na, Mg, and Si. We explored the absolute carbon abundances (A(C)) of CEMP stars in dSph galaxies and find similar behaviour to that seen for Milky Way halo CEMP stars, but highlight that CEMP-r/sstars primarily have very highA(C) values. We also compared the neutron-capture element abundances of the CEMP-r/sstars in our sample to recenti-process yields, which provide a good match to the derived abundances.
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 | 0.000 |
| 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".