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Record W7020627698

The LOFAR Two-metre Sky Survey III. First data release: Optical/infrared identifications and value-added catalogue

2019· article· en· W7020627698 on OpenAlexfundno aff

Bibliographic record

VenueLeiden Repository (Leiden University) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsnot available
FundersPlanetary Science DivisionScience and Technology Facilities CouncilObservatoire de Paris, Université de Recherche Paris Sciences et LettresScience Mission DirectorateSmithsonian Astrophysical ObservatoryJet Propulsion LaboratoryMax-Planck-Institut für AstronomieEötvös Loránd TudományegyetemCommonwealth Scientific and Industrial Research OrganisationMinisterium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-WestfalenMax-Planck-GesellschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekQueen's UniversityBundesministerium für Bildung und ForschungNational Science FoundationScience Foundation IrelandUniversity of California, Los AngelesUniversity of HertfordshireCentre National de la Recherche ScientifiqueUniversity of OxfordNational Central UniversityQueen's University BelfastGordon and Betty Moore FoundationUniversité d'OrléansLeverhulme TrustLos Alamos National LaboratoryAlfred P. Sloan FoundationJohns Hopkins UniversitySpace Telescope Science InstituteDurham UniversitySmithsonian InstitutionCalifornia Institute of TechnologyNational Aeronautics and Space Administration
KeywordsLOFARSkyIdentification (biology)GalaxyAssociation (psychology)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120-168 MHz survey of the northern sky with diverse and ambitious science goals. Many of the scientific objectives of LoTSS rely upon, or are enhanced by, the association or separation of the sometimes incorrectly catalogued radio components into distinct radio sources and the identification and characterisation of the optical counterparts to these sources. We present the source associations and optical and/or IR identifications for sources in the first data release, which are made using a combination of statistical techniques and visual association and identification. We document in detail the colour- and magnitude-dependent likelihood ratio method used for statistical identification as well as the Zooniverse project, called LOFAR Galaxy Zoo, used for visual classification. We describe the process used to select which of these two different methods is most appropriate for each LoTSS source. The final LoTSS-DR1-IDs value-added catalogue presented contains 318 520 radio sources, of which 231 716 (73%) have optical and/or IR identifications in Pan-STARRS and WISE.

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 score0.138
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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