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

Article, Preprint English OPEN
Mrowinski, Maciej J.; Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica;
(2017)
  • Publisher: Public Library of Science (PLoS)
  • Journal: PLoS ONE,volume 12,issue 9 (issn: 1932-6203, eissn: 1932-6203)
  • Publisher copyright policies & self-archiving
  • Related identifiers: pmc: PMC5607159, doi: 10.1371/journal.pone.0184711
  • Subject: Applied Mathematics | Algorithms | Science and Technology Workforce | Research Article | Mathematics | Evolutionary Algorithms | Professions | Computer Science - Digital Libraries | Careers in Research | Mathematical and Statistical Techniques | Simulation and Modeling | Population Groupings | Physical Sciences | Optimization | People and Places | Research Assessment | Crystallographic Techniques | Phase Determination | Science Policy | Computer Science - Neural and Evolutionary Computing | Mathematical Functions | Physics - Physics and Society | Research and Analysis Methods | Medicine | Evolutionary Computation | Q | R | Peer Review | Scientists | Science | Computational Techniques

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... View more
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