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Publish papers in machine-readable format with biomedical metadata

Just accepting papers in sci.AI JATS .xml format and placing it on the web page of the paper is a big step already. Announce that your journal accepts sci.AI JATS files from authors.
The files might be published next to PDF files

Hello Dear authors,
We are pleased to inform you that our journal supports machine-readable papers.
Please use sci.AI platform to semanticize your articles and send us the JATS file. We will publish the file addition to PDF file

Export paper in RDFa format to publish it directly or embed sci.AI JS add-on for JATS to HTML conversion

Future of the Academic Publishing

Future of research communication is not only a textual form. Each paper will be like a standalone application with possibility to reproduce described experiment , find hidden connections between papers, analyze results on interactive diagrams and even visit the virtual laboratory to make your own experiment

With the proper technology in use, Journals will become driving force of the literature based discovery and in silico research.

How to Approach the Future with sci.AI

sci.AI platform provides one of the most important components for this future – machine-readable research text with biomedical metadata.

Authors submit papers in enhanced format by sending sci.AI JATS or providing link to the paper’s preprint in app.sci.ai. Editorial team takes paper directly from here for the further processing. Journal can post-process already published papers too.

In result, papers are provided as separate JATS file and in HTML with biomedical metadata. So that algorithms and search engines read research description correctly, link it to the global knowledge graph and return relevant search results to the target audience

Is it free?

Yes, semanticization of the papers via the platform, our key service, is free. The idea is simple: if semanticization is free and widely accepted by scientists and publishers, then recipients of research reports will not lose thousands of hours on initial transformation of the plain biomedical texts into a machine-readable format.

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