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Artificial intelligence in peer review: How can evolutionary computation support journal editors?

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by p...

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Detalles Bibliográficos
Autores principales: Mrowinski, Maciej J., Fronczak, Piotr, Fronczak, Agata, Ausloos, Marcel, Nedic, Olgica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607159/
https://www.ncbi.nlm.nih.gov/pubmed/28931033
http://dx.doi.org/10.1371/journal.pone.0184711
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author Mrowinski, Maciej J.
Fronczak, Piotr
Fronczak, Agata
Ausloos, Marcel
Nedic, Olgica
author_facet Mrowinski, Maciej J.
Fronczak, Piotr
Fronczak, Agata
Ausloos, Marcel
Nedic, Olgica
author_sort Mrowinski, Maciej J.
collection PubMed
description With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems.
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spelling pubmed-56071592017-10-09 Artificial intelligence in peer review: How can evolutionary computation support journal editors? Mrowinski, Maciej J. Fronczak, Piotr Fronczak, Agata Ausloos, Marcel Nedic, Olgica PLoS One Research Article With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems. Public Library of Science 2017-09-20 /pmc/articles/PMC5607159/ /pubmed/28931033 http://dx.doi.org/10.1371/journal.pone.0184711 Text en © 2017 Mrowinski et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mrowinski, Maciej J.
Fronczak, Piotr
Fronczak, Agata
Ausloos, Marcel
Nedic, Olgica
Artificial intelligence in peer review: How can evolutionary computation support journal editors?
title Artificial intelligence in peer review: How can evolutionary computation support journal editors?
title_full Artificial intelligence in peer review: How can evolutionary computation support journal editors?
title_fullStr Artificial intelligence in peer review: How can evolutionary computation support journal editors?
title_full_unstemmed Artificial intelligence in peer review: How can evolutionary computation support journal editors?
title_short Artificial intelligence in peer review: How can evolutionary computation support journal editors?
title_sort artificial intelligence in peer review: how can evolutionary computation support journal editors?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607159/
https://www.ncbi.nlm.nih.gov/pubmed/28931033
http://dx.doi.org/10.1371/journal.pone.0184711
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