The extremely low-metallicity tail of the Sculptor dwarf spheroidal galaxy
Bibliographic record
Abstract
We present abundances for seven stars in the (extremely) low-metallicity tail of the Sculptor dwarf spheroidal galaxy, from spectra taken with X-shooter on the ESO VLT. Targets were selected from the Ca II triplet (CaT) survey of the dwarf abundances and radial velocities team (DART) using the latest calibration. Of the seven extremely metal-poor candidates, five stars are confirmed to be extremely metal-poor (i.e., [Fe/H] < −3 dex), with [Fe/H] = –3.47 ± 0.07 for our most metal-poor star. All have [Fe/H] ≤ −2.5 dex from the measurement of individual Fe lines. These values are in agreement with the CaT predictions to within error bars. None of the seven stars is found to be carbon-rich. We estimate a 2–13% possibility of this being a pure chance effect, which could indicate a lower fraction of carbon-rich extremely metal-poor stars in Sculptor compared to the Milky Way halo. The [α/Fe] ratios show a range from +0.5 to –0.5, a larger variation than seen in Galactic samples although typically consistent within 1–2σ. One star seems mildly iron-enhanced. Our program stars show no deviations from the Galactic abundance trends in chromium and the heavy elements barium and strontium. Sodium abundances are, however, below the Galactic values for several stars. Overall, we conclude that the CaT lines are a successful metallicity indicator down to the extremely metal-poor regime and that the extremely metal-poor stars in the Sculptor dwarf galaxy are chemically more similar to their Milky Way halo equivalents than the more metal-rich population of stars.
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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 | 0.001 | 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 | 0.001 |
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".