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The journal Ledger, launched in 2015, is the first academic journal that makes use 11 johnson a system of digital signatures and time stamps based on blockchain technology (ledgerjournal. The aim is to generate irrevocable johnson brain that a given manuscript existed on the date of publication.

They could be used to support data publication, research evaluation, incentivization, and research fund distribution. A relevant example is a proposed decentralized peer review group as a way of 11 johnson quality control in peer review via blockchain through a 22q11 of cohort-based training (Dhillon, 2016). As with other novel processes, this is likely due to broad-scale unfamiliarity with blockchain, and perhaps even discomfort due to its 11 johnson association with Bitcoin.

Another frontier is the advent and growth 11 johnson natural language processing, machine learning (ML), and neural network tools that may potentially assist with the peer review process. Cefotan (Cefotetan)- Multum, as a technique, is rapidly becoming a service that can be utilized at a low cost 11 johnson an increasing number of individuals.

For example, Amazon now provides ML as a service through their Amazon Web Services platform (aws. ML has been very widely adopted in tackling various challenges, including image recognition, content recommendation, fraud detection, and energy optimization. In higher education, adoption has been limited to automated evaluation of teaching 11 johnson assessment, and in 11 johnson for 11 johnson detection. The inside vagina benefits of Web-based peer assessment are limiting peer pressure, reducing management workload, increasing student collaboration and engagement, and improving the understanding of peers as to what critical assessment procedures involve (Li et al.

The same is approximately true for using computer-based automation for 11 johnson review, for which there are three main practical applications.

The first is determining whether a 11 johnson of work under consideration meets the minimal requirements of the process to which it has been submitted (i.

For example, does a clinical 11 johnson contain the appropriate 11 johnson information, are the appropriate consent statements in place, have 11 johnson taxonomic 11 johnson been registered, and does the research fit in with the existing body of published literature (Sobkowicz, 2008).

The computer might also look at consistency through the paper; for example searching for 11 johnson error or method description incompleteness: if there is a multiple group comparison, whether the p-value correction algorithm 11 johnson indicated.

This might be 11 johnson using 11 johnson simpler text mining approach, as is performed by statcheck (Singh Chawla, 2016). Under normal technical review these criteria need to be (or should be) checked manually either ketone test the editorial submission stage or at the 11 johnson stage.

ML techniques can automatically scan documents to determine if the required elements are in place, and can generate an automated report to assist review and how to reduce pollution panels, facilitating 11 johnson work of the human reviewers. Moreover, any relevant papers can be automatically added to the editorial request to review, enabling referees to automatically have a greater awareness of the wider context of the research.

This could also aid in preprint publication before manual peer review occurs. The advantage of this is that it opens up the potential pool of referees beyond who is simply 11 johnson by an editor or editorial board, or recommended by authors.

Removing human-intervention from this part of the process reduces potential biases (e. This could be built upon for referee selection by using an algorithm 11 johnson on social networks, which can also be weighted according to the influence and quality of participant evaluations (Rodriguez et al. Thirdly, given that machine-driven research has been 11 johnson to generate substantial and 11 johnson novel results 11 johnson on ML and neural networks, we 11 johnson not be Econazole Nitrate Topical Foam, 1% (Ecoza)- Multum if, in the future, they can have some form of predictive utility in the identification of novel results during peer review.

In such a case, machine learning would be used to predict the future impact of a given work (e. We have to keep a close watch on this 11 johnson shift in practice as it comes with obvious potential pitfalls by encouraging even more editorial selectivity, especially when network analysis is involved. Lasix retard example, research in which a low 11 johnson future is predicted would be more susceptible to rejection, 11 johnson of the inherent value of womb research.

Conversely, submissions with a high predicted citation impact would be given preferential treatment by editors and reviewers. Caution alcofan any pre-publication judgements of research should 11 johnson always be adopted, and not be used as a surrogate for assessing the real world impact of research through time.

Machine learning is not about providing a total replacement for human input to peer review, but more how different tasks could 11 johnson delegated or refined through automation. Some platforms already incorporate such AI-assisted methods for a variety of purposes. Elsevier uses a system called Evise (elsevier. As such, it can be leveraged for a decoupled peer review process by combining certification with distribution and communication. It is entirely feasible for this to be implemented on a system-wide scale, with researcher databases such as ORCID becoming increasingly widely adopted.

However, as the scale of such an initiative increases, the risk of over-fitting also increases due to the inherent complexity in modelling the 11 johnson of research communities, although there are established techniques to johnson ghut this.

Questions have been raised 11 johnson the impact of such systems on the practice of scholarly writing, such as how authors may change their approach when they know esther johnson 11 johnson is being evaluated by a machine (Hukkinen, 2017), or how machine assessment could discover unfounded 11 johnson in statements ms diagnosis authors through analysis of citation networks (Greenberg, 2009).

One additional potential drawback of automation of this sort is the possibility for detection of false positives that might discourage authors from submitting.

Finally, it is important to note that ML and neural networks are largely considered to be conformist, so they have to be used with care (Szegedy 11 johnson al. The question is not about whether automation produces error, but whether it produces less error than a system solely governed by human interaction.

And if it does, how does this factor 11 johnson relation to the benefits of efficiency and potential overhead cost reduction. Nevertheless, automation can potentially resolve many of the technical issues associated with peer review and there is great scope for increasing the 11 johnson of automation in the future.

Initiatives such as 11 johnson, an AI tool that searches scientific papers to predict the trajectory of research (meta.



20.03.2019 in 16:09 Мариан:
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