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Record W4288079920 · doi:10.1051/0004-6361/202037706

The<i>XMM-Newton</i>serendipitous survey

2020· article· en· W4288079920 on OpenAlexfundno aff
I. Traulsen, A. Schwope, G. Lamer, J. Ballet, F. J. Carrera, M. T. Ceballos, M. Coriat, M. J. Freyberg, F. Koliopanos, J. Kurpas, Laurent Michel, C. Motch, M. J. Page, M. G. Watson, N. A. Webb

Bibliographic record

VenueAstronomy and Astrophysics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratorySmithsonian Astrophysical ObservatoryUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieMax-Planck-Institut für AstrophysikCentre National d’Etudes SpatialesUniversity of OxfordYork UniversityCarnegie Institution for ScienceMinisterio de Ciencia, Innovación y UniversidadesLeibniz-GemeinschaftUniversity of Notre DameCarnegie Mellon UniversityUniversidad Nacional Autónoma de MéxicoAgencia Estatal de InvestigaciónYale UniversityDeutsches Zentrum für Luft- und RaumfahrtAlfred P. Sloan FoundationUniversity of WashingtonJohns Hopkins UniversityOhio State UniversityCarnegie Institution of WashingtonNational Science FoundationU.S. Department of EnergySmithsonian InstitutionMinistério da Ciência, Tecnologia e InovaçãoNational Aeronautics and Space AdministrationNew Mexico State UniversityUniversity of PortsmouthVanderbilt University
KeywordsPhysicsSkyAstrophysicsSmoothingSource countsBrightnessAstronomyGalaxyStatisticsRedshift

Abstract

fetched live from OpenAlex

Context. The XMM-Newton Survey Science Centre Consortium (SSC) develops software in close collaboration with the Science Operations Centre to perform a pipeline analysis of all XMM-Newton observations. In celebration of the twentieth anniversary of the XMM-Newton launch, the SSC has compiled the fourth generation of serendipitous source catalogues, 4XMM. Aims. The catalogue described here, 4XMM-DR9s, explores sky areas that were observed more than once by XMM-Newton . These observations are bundled in groups referred to as stacks. Stacking leads to a higher sensitivity, resulting in newly discovered sources and better constrained source parameters, and unveils long-term brightness variations. Methods. The 4XMM-DR9s catalogue was constructed from simultaneous source detection on overlapping observations. As a novel feature, positional rectification was applied beforehand. Observations with all filters and suitable camera settings were included. Exposures with a high background were discarded. The high-background thresholds were determined through a statistical analysis of all exposures in each instrument configuration. The X-ray background maps used in source detection were modelled via an adaptive smoothing procedure with newly determined parameters. Source fluxes were derived for all contributing observations, irrespective of whether the source would be detectable in an individual observation. Results. The new catalogue lists the X-ray sources detected in 1329 stacks with 6604 contributing observations over repeatedly covered 300 square degrees in the sky. Most stacks are composed of two observations, the largest one comprises 352 observations. We find 288 191 sources of which 218 283 were observed several times. The number of observations of a source ranges from 1 to 40. Auxiliary products, like X-ray full-band and false-colour images, long-term X-ray light curves, and optical finding charts, are published as well. Conclusions. 4XMM-DR9s contains new detections and is considered a prime resource to explore long-term variability of X-ray sources discovered by XMM-Newton . Regular incremental releases, including new public observations, are planned.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.005

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 head0.017
GPT teacher head0.214
Teacher spread0.197 · 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

Citations66
Published2020
Admission routes1
Has abstractyes

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