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Record W1925373677 · doi:10.1051/0004-6361/201526601

The first and second data releases of the Kilo-Degree Survey

2015· article· en· W1925373677 on OpenAlexafffund
J. T. A. de Jong, G. Verdoes Kleijn, Danny Boxhoorn, Hugo Buddelmeijer, Massimo Capaccioli, F. Getman, A. Grado, Ewout Helmich, Zhuoyi Huang, N. Irisarri, Konrad Kuijken, F. La Barbera, John McFarland, N. R. Napolitano, M. Radovich, G. Sikkema, E. A. Valentijn, K. Begeman, M. Brescia, S. Cavuoti, Oliver-Mark Cordes, G. Covone, M. Dall’Ora, H. Hildebrandt, G. Longo, Reiko Nakajima, M. Paolillo, E. Puddu, A. Rifatto, C. Tortora, Edo van Uitert, Axel Buddendiek, Joachim Harnois-Déraps, T. Erben, Martin Eriksen, Catherine Heymans, Henk Hoekstra, Benjamin Joachimi, T. Kitching, Dominik Klaes, L. V. E. Koopmans, F. Köhlinger, N. Roy, Cristobál Sifón, Peter Schneider, William J. Sutherland, Massimo Viola, Willem-Jan Vriend

Bibliographic record

VenueAstronomy and Astrophysics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of British Columbia
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekINAF-Osservatorio Astronomico di PadovaUniversità degli Studi di PadovaDeutsche ForschungsgemeinschaftMinistero dell’Istruzione, dell’Università e della RicercaScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsRedshiftRedshift surveyGalaxyPhotometry (optics)PhysicsSkyQuasarWeak gravitational lensingData qualityAstronomyRemote sensingPhotometric redshiftAstrophysicsGeographyStarsEngineering

Abstract

fetched live from OpenAlex

Context. The Kilo-Degree Survey (KiDS) is an optical wide-field imaging survey carried out with the VLT Survey Telescope and the OmegaCAM camera. KiDS will image 1500 square degrees in four filters (ugri), and together with its near-infrared counterpart VIKING will produce deep photometry in nine bands. Designed for weak lensing shape and photometric redshift measurements, its core science driver is mapping the large-scale matter distribution in the Universe back to a redshift of ~0.5. Secondary science cases include galaxy evolution, Milky Way structure, and the detection of high-redshift clusters and quasars.

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)0.008
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 score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.013

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 head0.030
GPT teacher head0.217
Teacher spread0.187 · 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

Citations305
Published2015
Admission routes2
Has abstractyes

Explore more

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