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Record W4308840582 · doi:10.1093/mnras/stac3244

Globular cluster ultraluminous X-ray sources in the furthest early-type galaxies

2022· article· en· W4308840582 on OpenAlexafffund
Erica Thygesen, Yifan Sun, Jeff Huang, Kristen C. Dage, Stephen E. Zepf, Arunav Kundu, Daryl Haggard, Thomas J. Maccarone

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill Space InstituteNational Science FoundationCommunal Studies AssociationSpace Telescope Science InstituteU.S. Nuclear Regulatory CommissionCanada Research ChairsNational Aeronautics and Space Administration
KeywordsPhysicsAstrophysicsGlobular clusterGalaxyLuminosityHubble space telescopeAccretion (finance)RADIUSGalaxy clusterAstronomy

Abstract

fetched live from OpenAlex

ABSTRACT Ultraluminous X-ray sources (ULXs) in globular clusters (GCs) are low-mass X-ray binaries that achieve high X-ray luminosities through a currently uncertain accretion mechanism. Using archival Chandra and Hubble Space Telescope observations, we perform a volume-limited search (≲70 Mpc) of 21 of the most massive ($\gt 10^{11.5} \, \mathrm{M}_\odot$) early-type galaxies to identify ULXs hosted by GC candidates. We find a total of 34 ULX candidates above the expected background within five times the effective radius of each galaxy, with 10 of these ($\sim 29.4{{\ \rm per\ cent}}$) potentially hosted by a GC. A comparison of the spatial and luminosity distributions of these new candidate GC ULXs with previously identified GC ULXs shows that they are similar: both samples peak at LX ∼ a few × 1039 erg s−1 and are typically located within a few effective radii of their host galaxies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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
Published2022
Admission routes2
Has abstractyes

Explore more

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