Nature Research Assistant covers literature discovery, reading support and writing guidance (a “Manuscript Adviser” mode for original research manuscripts). Built on a multi-publisher peer-reviewed corpus — not just Springer Nature content — designed with domain experts and aligned…
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NEJM Group’s beta AI article companion sits alongside individual NEJM articles to help with exploration, clarification and clinical interpretation. Deliberately constrained: it draws only on the article itself, no external sources, and is framed as assistive rather than…
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NEJM AI’s invitation-only Fast Track review process puts AI-generated peer review alongside human review, with an initial decision promised within 7 days. A human editor first writes a complete review independent of AI; the editor then uses two…
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Nicia.ai’s peer review assistant claims 95% time savings, positioned as agentic AI that makes autonomous decisions within defined parameters while deferring to human judgment on scientific merit.Notes & quotesThe 95% figure is the vendor’s own.
MDPI’s Online Proofreading platform lets external authors and MDPI staff finalise articles together in one system, replacing the email back-and-forth of traditional proofreading. In use across several MDPI journals.
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PLOS’s Open Science Indicators dataset, built with DataSeer, uses NLP and AI to identify and quantify open science practices in published literature. The fourth quarterly update covers January 2019 to June 2023 and adds a preliminary protocol-sharing indicator…
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OpenAIReview is an open-source, AI-assisted reviewing tool from the University of Chicago’s Human+AI (CHAI) Lab, built to give any researcher high-quality paper feedback “for less than the cost of a coffee”. It takes a full paper (PDF, markdown…
The Oxford Academic AI Discovery Assistant, built with Silverchair, adds semantic search with AI-generated summaries to the Oxford Academic platform, using RAG over metadata: titles, abstracts, keywords, publication dates.
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OUP used Hum’s Alchemist Taxonomy & Tagging Engine to run personalised call-for-papers campaigns: reader behaviour on Oxford Academic identified potential authors by topical interest, who then saw targeted pop-ups inviting manuscript submissions.
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Pangram Labs builds AI-text detection for researchers, educators and publishers: analysing text for AI characteristics, verifying originality and supporting transparent attribution, on the premise that AI tools are now a permanent part of writing workflows.
