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Record W2048873767 · doi:10.1088/0004-637x/777/1/69

A RADIO-SELECTED BLACK HOLE X-RAY BINARY CANDIDATE IN THE MILKY WAY GLOBULAR CLUSTER M62

2013· article· en· W2048873767 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlobular clusterMilky WayBlack hole (networking)JanskyStar clusterBinary black holeIntermediate-mass black holeStellar black hole

Abstract

fetched live from OpenAlex

We report the discovery of a candidate stellar-mass black hole in the Milky Way globular cluster M62. We detected the black hole candidate, which we term M62-VLA1, in the core of the cluster using deep radio continuum imaging from the Karl G. Jansky Very Large Array. M62-VLA1 is a faint source, with a flux density of 18.7 +/- 1.9 microJy at 6.2 GHz and a flat radio spectrum (alpha=-0.24 +/- 0.42, for S_nu = nu^alpha). M62 is the second Milky Way cluster with a candidate stellar-mass black hole; unlike the two candidate black holes previously found in the cluster M22, M62-VLA1 is associated with a Chandra X-ray source, supporting its identification as a black hole X-ray binary. Measurements of its radio and X-ray luminosity, while not simultaneous, place M62-VLA1 squarely on the well-established radio--X-ray correlation for stellar-mass black holes. In archival Hubble Space Telescope imaging, M62-VLA1 is coincident with a star near the lower red giant branch. This possible optical counterpart shows a blue excess, H alpha emission, and optical variability. The radio, X-ray, and optical properties of M62-VLA1 are very similar to those for V404 Cyg, one of the best-studied quiescent stellar-mass black holes. We cannot yet rule out alternative scenarios for the radio source, such as a flaring neutron star or background galaxy; future observations are necessary to determine whether M62-VLA1 is indeed an accreting stellar-mass black hole.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.844
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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 teacher head, 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

Citations138
Published2013
Admission routes1
Has abstractyes

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