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Record W2789899356 · doi:10.1051/0004-6361/201732176

LQAC-4: Fourth release of the Large Quasar Astrometric Catalogue

2018· article· en· W2789899356 on OpenAlexfundno aff
C. Gattano, A. H. Andrei, Bruno Coelho, J. Souchay, C. Barache, F. Taris

Bibliographic record

VenueAstronomy and Astrophysics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryConselho Nacional de Desenvolvimento Científico e TecnológicoYork UniversityCarnegie Mellon UniversityOffice of ScienceJohns Hopkins UniversityCollege of Engineering, Michigan State UniversityHarvard UniversityOhio State UniversityEuropean Space AgencyNational Science FoundationUniversity of WashingtonAlfred P. Sloan FoundationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityUniversity of ArizonaObservatoire de Paris, Université de Recherche Paris Sciences et LettresPrinceton UniversityBrookhaven National LaboratoryU.S. Department of Energy
KeywordsQuasarPhysicsAstrophysicsProper motionAstrometryAbsolute magnitudeContext (archaeology)AstronomyRedshiftStarsGalaxyGeography

Abstract

fetched live from OpenAlex

Context.From an astrometric point of view, quasars constitute the best and almost ideal reference objects in the celestial sphere, with a priori no significant proper motion. Since the third release of the Large Quasar Astrometric Catalogue (LQAC-3), a large number of quasars have been discovered, in particular those coming from the DR12Q release of the SDSS. Moreover, for cross-matched objects, we have taken advantage of the very accurate determinations of the quasars identified within the recentGaiaDR1 catalogue. Aims.Following the same procedure as in the three previous releases of the LQAC, our aim is to compile the large majority of all the quasars recorded so far. Our goal is to record their best coordinates and substantial information concerning their physical properties such as the redshift as well as multi-bands apparent and absolute magnitudes. Emphasis is given to the results of the cross-matches with theGaiaDR1 catalogue. Methods.New quasars coming from the DR12Q release were cross-matched with the precedent LQAC-3 compilation with a 1′′ search radius, in order to add the objects without counterpart to the LQAC-4 compilation. A similar cross-match was done withGaiaDR1 to identify the known quasars detected byGaia. This enables one to improve significantly the positioning of these objects, and in parallel to study the astrometric performance of the individual catalogues of the LQAC-4 compilation. Finally, a new method was used to determine absolute magnitudes. Results.Our final catalogue, called LQAC-4, contains 443 725 objects. This is roughly 37.82% more than the number of objects recorded in the LQAC-3. Among them, 249 071 were found in common with theGaiaDR1, with a 1′′ search radius. That corresponds to 56.13% of the whole population in the compilation. Conclusions.The LQAC-4 delivers to the astronomical community a nearly complete catalogue of spectroscopically confirmed quasars (including a small proportion of compact AGNs), with the aim of giving their best equatorial coordinates with respect to the ICRF2 and with exhaustive additional information. For more than 50% of the sample, these coordinates come from the very recentGaiaDR1.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0190.014
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.022

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 head0.006
GPT teacher head0.195
Teacher spread0.188 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations16
Published2018
Admission routes1
Has abstractyes

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