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Record W4391377584 · doi:10.3847/2041-8213/ad19c4

Spectacular Nucleosynthesis from Early Massive Stars

2024· article· en· W4391377584 on OpenAlexaff
Alexander P. Ji, Sanjana Curtis, Nicholas Storm, Vedant Chandra, Kevin C. Schlaufman, Keivan G. Stassun, Alexander Heger, M. Pignatari, Adrian M. Price-Whelan, M. Bergemann, Guy S. Stringfellow, Carla Fröhlich, Henrique Reggiani, Erika M. Holmbeck, Jamie Tayar, Shivani Shah, Emily J. Griffith, Chervin F. P. Laporte, Andrew R. Casey, Keith Hawkins, Danny Horta, W. Cerny, Pierre Thibodeaux, S. A. Usman, João A. S. Amarante, Rachael L. Beaton, Phillip A. Cargile, C. Chiappini, Charlie Conroy, Jennifer A. Johnson, Juna A. Kollmeier, Haining Li, Sarah Loebman, G. Meynet, Dmitry Bizyaev, Joel R. Brownstein, Pramod Gupta, Sean Morrison, Kaike Pan, Solange Ramírez, Hans‐Walter Rix, José Sánchez-Gallego

Bibliographic record

VenueThe Astrophysical Journal Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersNational Astronomical Observatories, Chinese Academy of SciencesLeibniz-GemeinschaftScience and Technology Facilities CouncilSmithsonian Astrophysical ObservatoryOffice of ScienceMax-Planck-Institut für AstronomieLeibniz-Institut für Astrophysik PotsdamNemzeti Kutatási Fejlesztési és Innovációs HivatalNuclear PhysicsNew Mexico State UniversityAstronomy Australia LimitedNanjing UniversityÉcole Polytechnique Fédérale de LausanneDeutsche ForschungsgemeinschaftJoint Institute for Nuclear Astrophysics - Center for the Evolution of the ElementsAlfred P. Sloan FoundationJohns Hopkins UniversityUniversity of HullHungarian Science FoundationCarnegie Institution of WashingtonUniversity of UtahSpace Telescope Science InstituteMagyar Tudományos AkadémiaHarvard UniversityOhio State UniversityOffice of International Science and EngineeringMax-Planck-GesellschaftNational Science FoundationAmerican Academy of Periodontology FoundationU.S. Department of EnergySmithsonian InstitutionChina National Textile and Apparel CouncilEuropean Commission
KeywordsPhysicsNucleosynthesisAstrophysicsStarsMetallicityStellar nucleosynthesisAstronomyBig Bang nucleosynthesisMilky WayReionizationLow MassGalaxyRedshift

Abstract

fetched live from OpenAlex

Abstract Stars that formed with an initial mass of over 50 M ⊙ are very rare today, but they are thought to be more common in the early Universe. The fates of those early, metal-poor, massive stars are highly uncertain. Most are expected to directly collapse to black holes, while some may explode as a result of rotationally powered engines or the pair-creation instability. We present the chemical abundances of J0931+0038, a nearby low-mass star identified in early follow-up of the SDSS-V Milky Way Mapper, which preserves the signature of unusual nucleosynthesis from a massive star in the early Universe. J0931+0038 has a relatively high metallicity ([Fe/H] = −1.76 ± 0.13) but an extreme odd–even abundance pattern, with some of the lowest known abundance ratios of [N/Fe], [Na/Fe], [K/Fe], [Sc/Fe], and [Ba/Fe]. The implication is that a majority of its metals originated in a single extremely metal-poor nucleosynthetic source. An extensive search through nucleosynthesis predictions finds a clear preference for progenitors with initial mass >50 M ⊙ , making J0931+0038 one of the first observational constraints on nucleosynthesis in this mass range. However, the full abundance pattern is not matched by any models in the literature. J0931+0038 thus presents a challenge for the next generation of nucleosynthesis models and motivates the study of high-mass progenitor stars impacted by convection, rotation, jets, and/or binary companions. Though rare, more examples of unusual early nucleosynthesis in metal-poor stars should be found in upcoming large spectroscopic surveys.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.007
GPT teacher head0.201
Teacher spread0.194 · 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 designSimulation or modeling
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

Citations24
Published2024
Admission routes1
Has abstractyes

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