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Record W7114041789

GW231123: A Binary Black Hole Merger with Total Mass 190–265 M ⊙

2025· article· en· W7114041789 on OpenAlexfundno aff

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersEuropean Social FundJapan Society for the Promotion of ScienceSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Technology Facilities CouncilNational Science and Technology CouncilEuropean Regional Development FundCentre National de la Recherche ScientifiqueICTP South American Institute for Fundamental ResearchMinistry of Science and ICT, South KoreaNemzeti Kutatási Fejlesztési és Innovációs HivatalNational Research FoundationVlaamse regeringNational Astronomical Observatory of JapanMinistry of Education, Culture, Sports, Science and TechnologyNatural Sciences and Engineering Research Council of CanadaMinistry of Education, IndiaConseil Régional, Île-de-FranceIsrael Science FoundationScottish Universities Physics AllianceNational Natural Science Foundation of ChinaNational Research Foundation of KoreaDivision of Human Resource DevelopmentKorea Astronomy and Space Science InstituteHungarian Scientific Research FundGeneralitat de CatalunyaGeneralitat ValencianaFonds Wetenschappelijk OnderzoekIstituto Nazionale di Fisica NucleareU.S. Department of EnergyNational Research, Development and Innovation OfficeGreat Southern Development Commission, Government of Western AustraliaAgencia Estatal de InvestigaciónKorea Institute of Science and Technology InformationNederlandse Organisatie voor Wetenschappelijk OnderzoekInstitute for Cosmic Ray Research, University of TokyoCouncil of Scientific and Industrial Research, IndiaFundacja na rzecz Nauki PolskiejAcademia SinicaAbdus Salam International Centre for Theoretical PhysicsLeverhulme TrustEuropean CommissionRussian Science FoundationScottish Funding CouncilNarodowa Agencja Wymiany AkademickiejCentres de Recerca de CatalunyaInstitut des Origines de LyonFonds De La Recherche Scientifique - FNRSMinisterio de Ciencia, Innovación y UniversidadesScience and Engineering Research BoardNational Science Foundation
KeywordsBinary black holeBlack hole (networking)Stellar black holeRedshiftIntermediate-mass black holeSpin-flipPrimordial black holeLuminosity
DOInot available

Abstract

fetched live from OpenAlex

On 2023 November 23, the two LIGO observatories both detected GW231123, a gravitational-wave signal consistent with the merger of two black holes with masses 137−18+23M⊙ and 101−50+22M⊙ (90% credible intervals), at a luminosity distance of 0.7–4.1 Gpc, a redshift of 0.40−0.25+0.27 , and with a network signal-to-noise ratio of ∼20.7. Both black holes exhibit high spins— 0.90−0.19+0.10 and 0.80−0.52+0.20 , respectively. A massive black hole remnant is supported by an independent ringdown analysis. Some properties of GW231123 are subject to large systematic uncertainties, as indicated by differences in the inferred parameters between signal models. The primary black hole lies within or above the theorized mass gap where black holes between 60–130 M⊙ should be rare, due to pair-instability mechanisms, while the secondary spans the gap. The observation of GW231123 therefore suggests the formation of black holes from channels beyond standard stellar collapse and that intermediate-mass black holes of mass ∼200 M⊙ form through gravitational-wave-driven mergers.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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