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Record W4391360585 · doi:10.3390/universe10020061

Changing-Look Narrow-Line Seyfert 1 Galaxies, their Detection with SVOM, and the Case of NGC 1566

2024· article· en· W4391360585 on OpenAlexaff
Dawei Xu, S. Komossa, D. Grupe, Jing Wang, L. P. Xin, Xiaohong Han, Jian‐Yan Wei, J. Y. Bai, E. Bon, F. Cangemi, B. Cordier, M. Dennefeld, Luigi Gallo, W. Kollatschny, Defeng Kong, M. W. Ochmann, Y. L. Qiu, N. Schartel

Bibliographic record

VenueUniverse · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsSaint Mary's University
FundersDeutsches Zentrum für Luft- und RaumfahrtNational Natural Science Foundation of ChinaMinistarstvo Prosvete, Nauke i Tehnološkog RazvojaUniversity of Leicester
KeywordsPhysicsGalaxySupermassive black holeAstrophysicsLine (geometry)Astronomy

Abstract

fetched live from OpenAlex

We discuss applications of the study of the new and barely explored class of changing-look (CL) narrow-line Seyfert 1 (NLS1) galaxies and comment on their detection with the space mission SVOM (Space Variable Objects Monitor). We highlight the case of NGC 1566, which is outstanding in many respects, for instance as one of the nearest known CL AGN undergoing exceptional outbursts. Its NLS1 nature is discussed, and we take it as a nearby prototype for systems that could be discovered and studied in the near future, including with SVOM. Finally, we briefly examine the broader implications and applications of CL events in NLS1 galaxies and show that such systems, once discovered in larger numbers, will greatly advance our understanding of the physics of the environment of rapidly growing supermassive black holes. This White Paper is part of a sequence of publications which explore aspects of our understanding of (CL) NLS1 galaxy physics with future missions.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.178
Teacher spread0.173 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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