Chemo-dynamics of outer halo dwarf stars, including <i>Gaia</i>-Sausage and <i>Gaia</i>-Sequoia candidates
Bibliographic record
Abstract
ABSTRACT The low-metallicity, kinematically interesting dwarf stars studied by Stephens & Boesgaard (2002, SB02) are re-examined using Gaia DR2 astrometry, and updated model atmospheres and atomic line data. New stellar parameters are determined based on the Gaia DR2 parallactic distances and Dartmouth Stellar Evolution Database isochrones. These are in excellent agreement with spectroscopically determined stellar parameters for stars with [Fe/H] > −2; however, large disagreements are found for stars with [Fe/H] ≤ −2, with offsets as large as ΔTeff ∼ +500 K and Δlog g ∼ +1.0. A subset of six stars (test cases) are analysed ab initio using high-resolution spectra with Keck HIRES and Gemini GRACES. This sub-sample is found to include two α-challenged dwarf stars, suggestive of origins in a low-mass, accreted dwarf galaxy. The orbital parameters for the entire SB02 sample are re-determined using Gaia DR2 data. We find 11 stars that are dynamically coincident with the Gaia-Sausage accretion event and another 17 with the Gaia-Sequoia event in action space. Both associations include low-mass, metal-poor stars with isochrone ages older than 10 Gyr. Two dynamical subsets are identified within Gaia-Sequoia. When these subsets are examined separately, a common knee in [α/Fe] is found for the Gaia-Sausage and low orbital energy Gaia-Sequoia stars. A lower metallicity knee is tentatively identified in the Gaia-Sequoia high orbital energy stars. If the metal-poor dwarf stars in these samples are true members of the Gaia-Sausage and Gaia-Sequoia events, then they present a unique opportunity to probe the earlier star formation histories of these systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".