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Record W2162406251 · doi:10.1086/497965

SDSS J102111.02+491330.4: A Newly Discovered Gravitationally Lensed Quasar

2006· article· en· W2162406251 on OpenAlexaff
Bart Pindor, Daniel J. Eisenstein, Michael D. Gregg, R. H. Becker, Naohisa Inada, Masamune Oguri, Patrick B. Hall, David E. Johnston, Gordon T. Richards, Donald P. Schneider, Edwin L. Turner, Guido Brasi, Philip M. Hinz, Matthew A. Kenworthy, Doug Miller, John C. Barentine, H. Brewington, J. Brinkmann, Michael Harvanek, S. J. Kleinman, J. Krzesiński, Dan Long, Eric H. Neilsen, Peter R. Newman, A. Nitta, Stephanie A. Snedden, Donald G. York

Bibliographic record

VenueThe Astronomical Journal · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsQuasarPhysicsAstrophysicsGravitational lensGalaxyRedshiftSkyLens (geology)AstronomyOVV quasarGravitationStrong gravitational lensingOptics

Abstract

fetched live from OpenAlex

We report follow-up observations of two gravitational lens candidates identified in the Sloan Digital Sky Survey (SDSS) dataset. We have confirmed that SDSS J102111.02+491330.4 is a previously unknown gravitationally lensed quasar. This lens system exhibits two images of a $z = 1.72$ quasar, with an image separation of $1{\farcs}14 \pm 0.04$. Optical and near-IR imaging of the system reveals the presence of the lensing galaxy between the two quasar images. Observations of SDSS J112012.12+671116.0 indicate that it is more likely a binary quasar than a gravitational lens. This system has two quasars at a redshift of $z = 1.49$, with an angular separation of $1{\farcs}49 \pm 0.02$. However, the two quasars have markedly different SEDs and no lens galaxy is apparent in optical and near-IR images of this system. We also present a list of 31 SDSS lens candidates which follow-up observations have confirmed are \textit{not} gravitational lenses.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.867

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.207
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 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

Citations36
Published2006
Admission routes1
Has abstractyes

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