title: Network-based statistics for a community driven transparent publication process.
abstract: The current publishing system with its merits and pitfalls is a mending topic for debate among scientists of various disciplines. Editors and reviewers alike, both face difficult decisions about the judgment of new scientific findings. Increasing interdisciplinary themes and rapidly changing dynamics in method development of each field make it difficult to be an "expert" with regard to all issues of a certain paper. Although unintended, it is likely that misunderstandings, human biases, and even outright mistakes can play an unfortunate role in final verdicts. We propose a new community-driven publication process that is based on network statistics to make the review, publication, and scientific evaluation process more transparent.
authors.affiliation: Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University Maastricht, Netherlands.
authors.forename: Jan
authors.initials: J
authors.lastname: Zimmermann
authors.forename: Alard
authors.initials: A
authors.lastname: Roebroeck
authors.forename: Kamil
authors.initials: K
authors.lastname: Uludag
authors.forename: Alexander T
authors.initials: AT
authors.lastname: Sack
authors.forename: Elia
authors.initials: E
authors.lastname: Formisano
authors.forename: Bernadette
authors.initials: B
authors.lastname: Jansma
authors.forename: Peter
authors.initials: P
authors.lastname: De Weerd
authors.forename: Rainer
authors.initials: R
authors.lastname: Goebel