GRACES observations of young [α/Fe]-rich stars
Bibliographic record
Abstract
We measure chemical abundance ratios and radial velocities in four massive (i.e. young) [α/Fe]-rich red giant stars using high-resolution high-S/N spectra from ESPaDOnS fed by Gemini-GRACES. Our differential analysis ensures that our chemical abundances are on the same scale as the Alves-Brito et al. (2010) study of bulge, thin, and thick disc red giants. We confirm that the program stars have enhanced [α/Fe] ratios and are slightly metal poor. Aside from lithium enrichment in one object, the program stars exhibit no chemical abundance anomalies when compared to giant stars of similar metallicity throughout the Galaxy. This includes the elements Li, O, Si, Ca, Ti, Cr, Ni, Cu, Ba, La, and Eu. Therefore, there are no obvious chemical signatures that can help to reveal the origin of these unusual stars. While our new observations show that only one star (not the Li-rich object) exhibits a radial velocity variation, simulations indicate that we cannot exclude the possibility that all four could be binaries. In addition, we find that two (possibly three) stars show evidence for an infrared excess, indicative of a debris disc. This is consistent with these young [α/Fe]-rich stars being evolved blue stragglers, suggesting their apparent young age is a consequence of a merger or mass transfer. We would expect a binary fraction of ~50 per cent or greater for the entire sample of these stars, but the signs of the circumbinary disc may have been lost since these features can have short time-scales. Radial velocity monitoring is needed to confirm the blue straggler origin.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".