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Record W2774235005 · doi:10.1051/0004-6361/201731606

The XXL Survey

2017· article· en· W2774235005 on OpenAlexaff
C. Adami, Paul Giles, E. Koulouridis, F. Pacaud, C. A. Caretta, M. Pierre, D. Eckert, M. E. Ramos-Ceja, F. Gastaldello, S. Fotopoulou, V. Guglielmo, C. Lidman, T. Sadibekova, A. Iovino, B. J. Maughan, L. Chiappetti, Sinan Aliş, B. Altieri, I. K. Baldry, D. Bottini, M. Birkinshaw, L. Pozzetti, M. J. I. Brown, O. Cucciati, Simon P. Driver, E. Elmer, S. Ettori, A. E. Evrard, L. Faccioli, B. R. Granett, Meiert W. Grootes, L. Guzzo, Andrew Hopkins, C. Horellou, J. P. Lefèvre, J. Liske, K. Małek, F. Marulli, S. Maurogordato, M. S. Owers, S. Paltani, Bianca M. Poggianti, M. Polletta, M. Plionis, A. Pollo, E. Pompei, T. J. Ponman, David Rapetti, M. Ricci, A. S. G. Robotham, R. Tuffs, L. A. M. Tasca, I. Valtchanov, D. Vergani, Glenn Wagner, J. P. Willis

Bibliographic record

VenueAstronomy and Astrophysics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Victoria
FundersJet Propulsion LaboratoryInstitut national des sciences de l'UniversMax-Planck-Institut für AstronomieCentre National de la Recherche ScientifiqueNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyAgence Nationale de la RechercheInstituto de Astrofísica de Andalucía
KeywordsAstrophysicsRedshiftCluster (spacecraft)PhysicsContext (archaeology)Flux (metallurgy)Galaxy clusterGalaxyCluster samplingSample (material)ChemistryPopulationGeographyComputer scienceThermodynamics

Abstract

fetched live from OpenAlex

Context. In the currently debated context of using clusters of galaxies as cosmological probes, the need for well-defined cluster samples is critical. Aims. The XXL Survey has been specifically designed to provide a well characterised sample of some 500 X-ray detected clusters suitable for cosmological studies. The main goal of present article is to make public and describe the properties of the cluster catalogue in its present state, as well as of associated catalogues of more specific objects such as super-clusters and fossil groups. Methods. Following from the publication of the hundred brightest XXL clusters, we now release a sample containing 365 clusters in total, down to a flux of a few 10 −15 erg s −1 cm −2 in the [0.5–2] keV band and in a 1′ aperture. This release contains the complete subset of clusters for which the selection function is well determined plus all X-ray clusters which are, to date, spectroscopically confirmed. In this paper, we give the details of the follow-up observations and explain the procedure adopted to validate the cluster spectroscopic redshifts. Considering the whole XXL cluster sample, we have provided two types of selection, both complete in a particular sense: one based on flux-morphology criteria, and an alternative based on the [0.5–2] keV flux within 1 arcmin of the cluster centre. We have also provided X-ray temperature measurements for 80% of the clusters having a flux larger than 9 × 10 −15 erg s −1 cm −2 . Results. Our cluster sample extends from z ~ 0 to z ~ 1.2, with one cluster at z ~ 2. Clusters were identified through a mean number of six spectroscopically confirmed cluster members. The largest number of confirmed spectroscopic members in a cluster is 41. Our updated luminosity function and luminosity–temperature relation are compatible with our previous determinations based on the 100 brightest clusters, but show smaller uncertainties. We also present an enlarged list of super-clusters and a sample of 18 possible fossil groups. Conclusions. This intermediate publication is the last before the final release of the complete XXL cluster catalogue when the ongoing C2 cluster spectroscopic follow-up is complete. It provides a unique inventory of medium-mass clusters over a 50 deg 2 area out to z ~ 1.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0550.036

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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

Citations127
Published2017
Admission routes1
Has abstractyes

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