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Record W4413093339 · doi:10.3847/1538-4357/ade4ce

C-19 and Hot, Wide Star Streams

2025· article· en· W4413093339 on OpenAlexfundno aff
R. G. Carlberg, Rodrigo Ibata, Nicolas F. Martin, Else Starkenburg, David S. Aguado, Khyati Malhan, Kim A. Venn, Zhen Yuan

Bibliographic record

VenueThe Astrophysical Journal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersNational Science and Technology CouncilScience and Technology Facilities CouncilNational Tsing Hua UniversityVillum FondenUniversity of TorontoNederlandse Organisatie voor Wetenschappelijk OnderzoekDurham UniversityGovernment of Ontario
KeywordsPhysicsGlobular clusterMilky WayAstrophysicsGalactic haloVelocity dispersionAstronomyStar clusterPopulationDark matter haloHaloGalaxy

Abstract

fetched live from OpenAlex

Abstract The C-19 star stream has the abundance characteristics of an unusually metal-poor globular cluster but kinematically is uncharacteristically hot and wide for a cluster stream, having a line-of-sight velocity dispersion of 7 ± 2 km s−1 and a 1σ width of 240 pc. We show that the tidal dissolution of an old, lower-mass globular cluster in a cold dark matter (CDM) galactic halo can create a hot, wide stream currently near orbital apocenter. A cosmological Milky Way n-body simulation motivates the parameters for an evolving Milky Way halo potential containing an orbiting subhalo population in which we model a star cluster progenitor of C-19. The same model parameters have been used for a GD-1 stream model. The ∼7 km s−1 velocity dispersion is readily accomplished with an evolving CDM subhalo population, a progenitor cluster mass ≃2 × 104 M ⊙, and an orbit that keeps the progenitor orbital pericenter within about 10 kpc of the Milky Way dark halo or its precursors.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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