THE DUAL ORIGIN OF STELLAR HALOS. II. CHEMICAL ABUNDANCES AS TRACERS OF FORMATION HISTORY
Bibliographic record
Abstract
Fully cosmological, high-resolution N -body+smooth particle hydrodynamic simulations are used to investigate the chemical abundance trends of stars in simulated stellar halos as a function of their origin. These simulations employ a physically motivated supernova feedback recipe, as well as metal enrichment, metal cooling, and metal diffusion. As presented in an earlier paper, the simulated galaxies in this study are surrounded by stellar halos whose inner regions contain both stars accreted from satellite galaxies and stars formed in situ in the central regions of the main galaxies and later displaced by mergers into their inner halos. The abundance patterns ([Fe/H] and [O/Fe]) of halo stars located within 10 kpc of a solar-like observer are analyzed. We find that for galaxies which have not experienced a recent major merger, in situ stars at the high [Fe/H] end of the metallicity distribution function are more [α/Fe]-rich than accreted stars at similar [Fe/H]. This dichotomy in the [O/Fe] of halo stars at a given [Fe/H] results from the different potential wells within which in situ and accreted halo stars form. These results qualitatively match recent observations of local Milky Way halo stars. It may thus be possible for observers to uncover the relative contribution of different physical processes to the formation of stellar halos by observing such trends in the halo populations of the Milky Way and other local L ⋆ galaxies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".