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Unblinded Data for PLAsTiCC Classification Challenge

Name: Unblinded Data for PLAsTiCC Classification Challenge
Keywords: Transients, Astronomy, Classification, Simulation

Research datakeyboard_double_arrow_right Dataset 21 Jan 2019 English Publisher:Zenodo

Authors: PLASTICC Team; PLASTICC Modelers;

doi: 10.5281/zenodo.2539456 , 10.5281/zenodo.2535746

Unblinded Data for PLAsTiCC Classification Challenge

- Summary
- Subjects
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- Metrics

Abstract

Funding provided by: US National Science Foundation (NSF), US Department of Energy (DOE), Association of Universities for Research in Astronomy (AURA), Stanford Linear Accelerator Center (SLAC), LSST Corporation (LSSTc), LSST Dark Energy Science Collaboration (LSST-DESC), LSST Transients and Variables Stars Science Collaboration (LSST-TVS), Kaggle.

For classification challenge (https://plasticc.org), the unblinded data files are included here. See PDF note above for more information. The original challenge (Sep 28, 2018 - Dec 17, 2018) was hosted at https://www.kaggle.com/c/PLAsTiCC-2018 .

{"references": ["PLASTICC Team, \"The PLASTICC Data Set,\" https://arxiv.org/abs/1810.00001"]}

Keywords

Transients, Astronomy, Classification, Simulation

1 Research products, page 1 of 1

Unblinded metaData for PLAsTiCC Classification Challenge
2019HasVersion

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	5
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%