Convert .doc or .pdf Paper to JATS, HTML and RDF Automatically
Papers are enriched with biomedical meta tags and then serialized in W3C compatible JATS (RDF/XML), HTML+RDFa or RDF formats. Export in custom formats can be implemented on demand.
Read more about how to access semanticized papers via API

Contact us to find out more about integration of automatic metatagging into your publishing process
Increase Paper’s Rank in Search Engines by Publishing Paper in HTML+RDFa With Biomedical Microdata
Nothing confuses search engines more than plain text “hedgehog”

sci.AI addresses this issue with enhanced HTML+RDFa. Search engines read microdata of the web paper and link text chunks to the standard definitions in external ontologies unambiguously

Label Every Term and Interaction
First, sciAI NLP Engine assigns IDs from ontologies to the relevant terms. For example, lexical form “tryptophan hydroxylase” is the concept in the Uniprot ontology with ID=Q8IWU9. Then, Engine identifies which relationships and interactions with this concept are described in the text

User-friendly Validation Interface
100% precise semanticization is easily achievable with sci.AI validation UI
100% precise semanticization is easily achievable with sci.AI validation UI
Scientific Literature CAN be Easy to Understand
When in doubt or interested, scientists routinely use Wikipedia and Google search, where they type or cut/paste terms from papers. This is inefficient though, as they probably scan 50-100 scientific papers a month and read in depth 10-30
Give everything readers want directly on your journal’s page

Start using sci.AI in publishing process with one of the next options
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Publish each paper in machine-readable sci.AI JATS format next to the .pdf.
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Publish paper in HTML with biomedical microdata.
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Integrate sci.AI with electronic publishing platform
Find Papers to Complement and Expand Portfolio *
Predefine biomedical objects and categories of interest to receive alert about new preprint paper. Track all new discoveries to close gaps in portfolio
Plagiarism Detection and Facts Validation *
sci.AI decomposes each paper into “molecules of knowledge”. Then each “molecule” is placed into global knowledge graph that contains majority of published papers so far. You can validate each fact on a very granular level whether it is supported by evidence and how original research is