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Record W2920014427 · doi:10.3847/1538-4357/ab0c02

The R-Process Alliance: Discovery of a Low-α, r-process-enhanced Metal-poor Star in the Galactic Halo

2019· article· en· W2920014427 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Victoria
FundersScience and Technology Facilities Council
KeywordsMilky WayGalaxyStarsHaloGalactic haloDwarf galaxyGalactic coronaGalactic tideStellar kinematics

Abstract

fetched live from OpenAlex

Abstract A new moderately r-process-enhanced metal-poor star, RAVE J093730.5−062655, has been identified in the Milky Way halo as part of an ongoing survey by the R-Process Alliance. The temperature and surface gravity indicate that J0937−0626 is likely a horizontal branch star. At [Fe/H] = −1.86, J0937−0626 is found to have subsolar [X/Fe] ratios for nearly every light, α, and Fe-peak element. The low [α/Fe] ratios can be explained by an ∼0.6 dex excess of Fe; J0937−0626 is therefore similar to the subclass of “iron-enhanced” metal-poor stars. A comparison with Milky Way field stars at [Fe/H] = −2.5 suggests that J0937−0626 was enriched in material from an event, possibly a Type Ia supernova, that created a significant amount of Cr, Mn, Fe, and Ni and smaller amounts of Ca, Sc, Ti, and Zn. The r-process enhancement of J0937−0626 is likely due to a separate event, which suggests that its birth environment was highly enriched in r-process elements. The kinematics of J0937−0626, based on Gaia DR2 data, indicate a retrograde orbit in the Milky Way halo; J0937−0626 was therefore likely accreted from a dwarf galaxy that had significant r-process enrichment.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.244
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2019
Admission routes1
Has abstractyes

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