Variable stars in Local Group Galaxies – I. Tracing the early chemical enrichment and radial gradients in the Sculptor dSph with RR Lyrae stars
Bibliographic record
Abstract
We identified and characterized the largest (536) RR Lyrae (RRL) sample in a Milky Way dSph satellite (Sculptor) based on optical photometry data collected over ∼24 years. The RRLs display a spread in V-magnitude (∼0.35 mag) which appears larger than photometric errors and the horizontal branch (HB) luminosity evolution of a mono-metallic population. Using several calibrations of two different reddening free and metal independent period–Wesenheit relations we provide a new distance estimate μ = 19.62 mag (σμ = 0.04 mag) that agrees well with literature estimates. We constrained the metallicity distribution of the old population, using the MI period–luminosity relation, and we found that it ranges from −2.3 to −1.5 dex. The current estimate is narrower than suggested by low and intermediate spectroscopy of RGBs (Δ [Fe/H]≤ 1.5). We also investigated the HB morphology as a function of the galactocentric distance. The HB in the innermost regions is dominated by red HB stars and by RRLs, consistent with a more metal-rich population, while in the outermost regions it is dominated by blue HB stars and RRLs typical of a metal-poor population. Our results suggest that fast chemical evolution occurred in Sculptor, and that the radial gradients were in place at an early epoch.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".