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A transient search using combined human and machine classifications

Abstract:

Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been put into the development of automatic algorithms, but surveys still rely on human review of targets. This paper presents an integrated system for the identification of supernovae in data from Pan-STARRS1, combining classifications from volunteers participating in a citizen science project with those from a c...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1093/mnras/stx1812

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Physics; Astrophysics
Oxford college:
Mansfield College
Role:
Author
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National Aeronautics and Space Administration More from this funder
National Science Foundation More from this funder
Publisher:
Oxford University Press Publisher's website
Journal:
Monthly Notices of the Royal Astronomical Society Journal website
Volume:
472
Issue:
2
Pages:
1315-1323
Publication date:
2017-07-05
Acceptance date:
2017-07-17
DOI:
EISSN:
1365-2966
ISSN:
0035-8711
Pubs id:
pubs:709939
URN:
uri:32f1a456-995f-4916-996c-bd9a280e28df
UUID:
uuid:32f1a456-995f-4916-996c-bd9a280e28df
Local pid:
pubs:709939

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