Can your paper evade the editors axe? Towards an AI assisted peer review system

Authors : Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Srinivasa Satya Sameer Kumar Chivukula, Georgios Tsatsaronis, Pascal Coupet, Michelle Gregory

This work is an exploratory study of how we could progress a step towards an AI assisted peer- review system. The proposed approach is an ambitious attempt to automate the Desk-Rejection phenomenon prevalent in academic peer review.

In this investigation we first attempt to decipher the possible reasons of rejection of a scientific manuscript from the editors desk. To seek a solution to those causes, we combine a flair of information extraction techniques, clustering, citation analysis to finally formulate a supervised solution to the identified problems.

The projected approach integrates two important aspects of rejection: i) a paper being rejected because of out of scope and ii) a paper rejected due to poor quality. We extract several features to quantify the quality of a paper and the degree of in-scope exploring keyword search, citation analysis, reputations of authors and affiliations, similarity with respect to accepted papers.

The features are then fed to standard machine learning based classifiers to develop an automated system. On a decent set of test data our generic approach yields promising results across 3 different journals.

The study inherently exhibits the possibility of a redefined interest of the research community on the study of rejected papers and inculcates a drive towards an automated peer review system.


The Social Structure of Consensus in Scientific Review

Authors : Misha Teplitskiy, Daniel Acuna, Aida Elamrani-Raoult, Konrad Kording, James Evans

Personal connections between creators and evaluators of scientific works are ubiquitous, and the possibility of bias ever-present. Although connections have been shown to bias prospective judgments of (uncertain) future performance, it is unknown whether such biases occur in the much more concrete task of assessing the scientific validity of already completed work, and if so, why.

This study presents evidence that personal connections between authors and reviewers of neuroscience manuscripts are associated with biased judgments and explores the mechanisms driving the effect.

Using reviews from 7,981 neuroscience manuscripts submitted to the journal PLOS ONE, which instructs reviewers to evaluate manuscripts only on scientific validity, we find that reviewers favored authors close in the co-authorship network by ~0.11 points on a 1.0 – 4.0 scale for each step of proximity.

PLOS ONE’s validity-focused review and the substantial amount of favoritism shown by distant vs. very distant reviewers, both of whom should have little to gain from nepotism, point to the central role of substantive disagreements between scientists in different « schools of thought. »

The results suggest that removing bias from peer review cannot be accomplished simply by recusing the closely-connected reviewers, and highlight the value of recruiting reviewers embedded in diverse professional networks.


“Let the community decide”? The vision and reality of soundness-only peer review in open-access mega-journals

Authors : Valerie Spezi, Simon Wakeling, Stephen Pinfield, Jenny Fry, Claire Creaser, Peter Willett


The purpose of this paper is to better understand the theory and practice of peer review in open-access mega-journals (OAMJs). OAMJs typically operate a “soundness-only” review policy aiming to evaluate only the rigour of an article, not the novelty or significance of the research or its relevance to a particular community, with these elements being left for “the community to decide” post-publication.


The paper reports the results of interviews with 31 senior publishers and editors representing 16 different organisations, including 10 that publish an OAMJ. Thematic analysis was carried out on the data and an analytical model developed to explicate their significance.


Findings suggest that in reality criteria beyond technical or scientific soundness can and do influence editorial decisions. Deviations from the original OAMJ model are both publisher supported (in the form of requirements for an article to be “worthy” of publication) and practice driven (in the form of some reviewers and editors applying traditional peer review criteria to OAMJ submissions). Also publishers believe post-publication evaluation of novelty, significance and relevance remains problematic.


The study is based on unprecedented access to senior publishers and editors, allowing insight into their strategic and operational priorities.

The paper is the first to report in-depth qualitative data relating specifically to soundness-only peer review for OAMJs, shedding new light on the OAMJ phenomenon and helping inform discussion on its future role in scholarly communication. The paper proposes a new model for understanding the OAMJ approach to quality assurance, and how it is different from traditional peer review.

URL : “Let the community decide”? The vision and reality of soundness-only peer review in open-access mega-journals


Survey on open peer review: Attitudes and experience amongst editors, authors and reviewers

Authors : Tony Ross-Hellauer, Arvid Deppe, Birgit Schmidt

Open peer review (OPR) is a cornerstone of the emergent Open Science agenda. Yet to date no large-scale survey of attitudes towards OPR amongst academic editors, authors, reviewers and publishers has been undertaken.

This paper presents the findings of an online survey, conducted for the OpenAIRE2020 project during September and October 2016, that sought to bridge this information gap in order to aid the development of appropriate OPR approaches by providing evidence about attitudes towards and levels of experience with OPR.

The results of this cross-disciplinary survey, which received 3,062 full responses, show the majority (60.3%) of respondents to be believe that OPR as a general concept should be mainstream scholarly practice (although attitudes to individual traits varied, and open identities peer review was not generally favoured). Respondents were also in favour of other areas of Open Science, like Open Access (88.2%) and Open Data (80.3%).

Among respondents we observed high levels of experience with OPR, with three out of four (76.2%) reporting having taken part in an OPR process as author, reviewer or editor.

There were also high levels of support for most of the traits of OPR, particularly open interaction, open reports and final-version commenting. Respondents were against opening reviewer identities to authors, however, with more than half believing it would make peer review worse.

Overall satisfaction with the peer review system used by scholarly journals seems to strongly vary across disciplines. Taken together, these findings are very encouraging for OPR’s prospects for moving mainstream but indicate that due care must be taken to avoid a “one-size fits all” solution and to tailor such systems to differing (especially disciplinary) contexts.

OPR is an evolving phenomenon and hence future studies are to be encouraged, especially to further explore differences between disciplines and monitor the evolution of attitudes.

URL : Survey on open peer review: Attitudes and experience amongst editors, authors and reviewers


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

Authors : Maciej J. Mrowinski, Piotr Fronczak, Agata Fronczak, Marcel Ausloos, Olgica Nedic

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.


Preventing the ends from justifying the means: withholding results to address publication bias in peer-review

Authors : Katherine S. Button, Liz Bal, Anna Clark, Tim Shipley

The evidence that many of the findings in the published literature may be unreliable is compelling. There is an excess of positive results, often from studies with small sample sizes, or other methodological limitations, and the conspicuous absence of null findings from studies of a similar quality.

This distorts the evidence base, leading to false conclusions and undermining scientific progress. Central to this problem is a peer-review system where the decisions of authors, reviewers, and editors are more influenced by impressive results than they are by the validity of the study design.

To address this, BMC Psychology is launching a pilot to trial a new ‘results-free’ peer-review process, whereby editors and reviewers are blinded to the study’s results, initially assessing manuscripts on the scientific merits of the rationale and methods alone.

The aim is to improve the reliability and quality of published research, by focusing editorial decisions on the rigour of the methods, and preventing impressive ends justifying poor means.

URL : Preventing the ends from justifying the means: withholding results to address publication bias in peer-review


Does Peer Review Identify the Best Papers? A Simulation Study of Editors, Reviewers, and the Scientific Publication Process

Author : Justin Esarey

How does the structure of the peer review process, which can vary among journals, influence the quality of papers published in a journal? This article studies multiple systems of peer review using computational simulation. I find that, under any of the systems I study, a majority of accepted papers are evaluated by an average reader as not meeting the standards of the journal.

Moreover, all systems allow random chance to play a strong role in the acceptance decision. Heterogeneous reviewer and reader standards for scientific quality drive both results. A peer review system with an active editor—that is, one who uses desk rejection before review and does not rely strictly on reviewer votes to make decisions—can mitigate some of these effects.