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A web app that uses machine learning to recommend the most suitable journals based on the text content of your preprint

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Preprint Similarity Search

⭐ OPEN THE APP to start using the tool right away

📜 READ THE MANUSCRIPT for technical details on the machine learning model behind the tool

🤖 USE THE API like https://api-pss.greenelab.com/doi/YOUR-DOI

Based on the work and classifiers in the AnnoRxiver project

About

This tool uses a machine learning model trained on 2.3 million PubMed Central open access documents to find similar papers and journals based on the textual content of your bioRxiv or medRxiv preprint. These results can be used as a starting point when searching for a place to publish your paper.

The tool also provides a "map" of the PubMed Central documents, grouped into bins based on similar textual content, and shows you where your preprint falls on the map. Select a square to learn more about the papers in that bin.

The map also incorporates a set of 50 principal components (PCs) generated from bio/medRxiv. Each PC represents two high level concepts characterized by keywords of various strengths, illustrated in the word cloud thumbnails above the map. Select a thumbnail to color the map by that PC. Deeper orange squares will be papers that correlate more with the orange keywords in the image, and vice versa for blue.

About

A web app that uses machine learning to recommend the most suitable journals based on the text content of your preprint

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