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Frontiers in Computational Neuroscience
Article . 2012 . Peer-reviewed
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Frontiers in Computational Neuroscience
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Article . 2012
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Frontiers in Computational Neuroscience
Article . 2012 . Peer-reviewed
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DBLP
Article . 2012
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Open Peer Review by a Selected-Papers Network

Authors: Lee, Christopher;

Open Peer Review by a Selected-Papers Network

Abstract

A selected-papers (SP) network is a network in which researchers who read, write, and review articles subscribe to each other based on common interests. Instead of reviewing a manuscript in secret for the Editor of a journal, each reviewer simply publishes his review (typically of a paper he wishes to recommend) to his SP network subscribers. Once the SP network reviewers complete their review decisions, the authors can invite any journal editor they want to consider these reviews and initial audience size, and make a publication decision. Since all impact assessment, reviews, and revisions are complete, this decision process should be short. I show how the SP network can provide a new way of measuring impact, catalyze the emergence of new subfields, and accelerate discovery in existing fields, by providing each reader a fine-grained filter for high-impact. I present a three phase plan for building a basic SP network, and making it an effective peer review platform that can be used by journals, conferences, users of repositories such as arXiv, and users of search engines such as PubMed. I show how the SP network can greatly improve review and dissemination of research articles in areas that are not well-supported by existing journals. Finally, I illustrate how the SP network concept can work well with existing publication services such as journals, conferences, arXiv, PubMed, and online citation management sites.

Keywords

Publishing, Peer Review, Neuroscience (miscellaneous), Neurosciences. Biological psychiatry. Neuropsychiatry, open evaluation, scientometrics, Cellular and Molecular Neuroscience, publishing, interdisciplinary research, peer review, journal, RC321-571, Neuroscience

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    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).
    52
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 1%
Green
gold