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Record W2036589096 · doi:10.1086/375650

Host Galaxies of 2MASS-selected QSOs to Redshift 0.3

2003· article· en· W2036589096 on OpenAlexaff
J. B. Hutchings, Natasha Maddox, R. M. Cutri, B. Nelson

Bibliographic record

VenueThe Astronomical Journal · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsAstrophysicsPhysicsGalaxyActive galactic nucleusQSOSRedshiftSkyPopulationRedshift surveyAstronomyMedicine

Abstract

fetched live from OpenAlex

We present and discuss optical imaging of 76 active galactic nuclei (AGNs) that represent the selected Two Micron All Sky Survey (2MASS) sample for z < 0.3, from a full list of 243. They are found to have dust-obscured nuclei, residing in host galaxies that show a high fraction (greater than 70%) of tidal interactions. The derived luminosities of the AGNs and host galaxies are similar to traditionally selected AGNs, and they may comprise some 40% of the total AGN population at low redshift. We have measured a number of host galaxy properties and discuss their distributions and interrelations. We compare the 2MASS AGNs with optically selected samples and the IRAS -selected galaxy samples and discuss the differences in terms of merger processes and initial conditions.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.211
Teacher spread0.203 · 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

Citations30
Published2003
Admission routes1
Has abstractyes

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