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Record W2978472770 · doi:10.3847/2041-8213/ab4b4f

HSC-XD 52: An X-Ray Detected AGN in a Low-mass Galaxy at z ∼ 0.56

2019· article· en· W2978472770 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsHerzberg Institute of AstrophysicsSaint Mary's University
Fundersnot available
KeywordsSupermassive black holeGalaxyActive galactic nucleusLuminosityDwarf galaxyRedshiftSpectral energy distribution

Abstract

fetched live from OpenAlex

Abstract The properties of low-mass galaxies hosting central black holes provide clues about the formation and evolution of the progenitors of supermassive black holes. In this Letter, we present HSC-XD 52, a spectroscopically confirmed low-mass active galactic nucleus (AGN) at an intermediate redshift of z ∼ 0.56. We detect this object as a very luminous X-ray source coincident with a galaxy observed by the Hyper Suprime-Cam (HSC) as part of a broader search for low-mass AGN. We constrain its stellar mass through spectral energy distribution modeling to be LMC-like at M ⋆ ≈ 3 × 109 M ⊙, placing it in the dwarf regime. We estimate a central black hole mass of M BH ∼ 106 M ⊙. With an average X-ray luminosity of , HSC-XD 52 is among the most luminous X-ray selected AGN in dwarf galaxies. The spectroscopic and photometric properties of HSC-XD 52 indicate that it is an intermediate-redshift counterpart to local low-mass AGN.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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