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Record W4391450689 · doi:10.3390/universe10020069

X-ray Properties of Two Complementary Samples of Intermediate Seyfert Galaxies

2024· article· en· W4391450689 on OpenAlexfundno aff
B. Dalla Barba, L. Foschini, M. Berton, Luca Crepaldi, A. Vietri

Bibliographic record

VenueUniverse · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
FundersLeibniz-GemeinschaftLeibniz-Institut für Astrophysik PotsdamJet Propulsion LaboratoryNational Astronomical Observatories, Chinese Academy of SciencesUniversity of Illinois at Urbana-ChampaignSmithsonian Astrophysical ObservatoryMax-Planck-Institut für AstronomieNew Mexico State UniversityNanjing UniversityYale UniversityUniversity of TorontoÉcole Polytechnique Fédérale de LausanneSpace Telescope Science InstituteJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahHarvard UniversityOhio State UniversityChina National Textile and Apparel CouncilYunnan UniversityCalifornia Institute of TechnologyUniversity of Colorado BoulderNational Aeronautics and Space AdministrationSmithsonian Institution
KeywordsPhysicsGalaxyAstrophysicsAstronomyActive galactic nucleusX-rayNuclear physics

Abstract

fetched live from OpenAlex

We present the X-ray spectral analysis of two complementary sets of intermediate Seyfert galaxies (ISs). Analyzing X-ray data, we estimate the hydrogen abundance NH and test its connection with the [O III] luminosity acquired from optical observations. The results confirm the conclusions drawn in a previous study concerning the lack of a direct correlation between the obscuration measure (NH) and the intrinsic characteristics of the active nuclei ([O III] luminosity). Instead, we validate the existence of a correlation between the Seyfert type and the NH parameter, employing a separation threshold of approximately 1022 atoms cm−2. Simultaneously, our findings align with prior research, corroborating the relationship between X-ray luminosity and the [O III] luminosity.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.238
Teacher spread0.210 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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