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Preprints allow researchers to make their findings available to the scientific community before they have undergone peer review. Studies on preprints within bioRxiv have been largely focused on article metadata and how often these preprints are downloaded, cited, published, and discussed online. A missing element that has yet to be examined is the language contained within the bioRxiv preprint repository. We sought to compare and contrast linguistic features within bioRxiv preprints to published biomedical text as a whole as this is an excellent opportunity to examine how peer review changes these documents. The most prevalent features that changed appear to be associated with typesetting and mentions of supporting information sections or additional files. In addition to text comparison, we created document embeddings derived from a preprint-trained word2vec model. We found that these embeddings are able to parse out different scientific approaches and concepts, link unannotated preprint–peer-reviewed article pairs, and identify journals that publish linguistically similar papers to a given preprint. We also used these embeddings to examine factors associated with the time elapsed between the posting of a first preprint and the appearance of a peer-reviewed publication. We found that preprints with more versions posted and more textual changes took longer to publish. Lastly, we constructed a web application (https://greenelab.github.io/preprint-similarity-search/) that allows users to identify which journals and articles that are most linguistically similar to a bioRxiv or medRxiv preprint as well as observe where the preprint would be positioned within a published article landscape., Preprints allow researchers to make their findings available to the scientific community before they have undergone peer review This study analyzes the full text content of the bioRxiv preprint repository, identifying field-specific patterns and changes that occur during publication, and providing a search tool that can identify the published papers that are most similar to a given bioRxiv or medRxiv preprint.

Additional file 1: Figure S1. An example of restoration of brittle silver artifact by conventional thermal treatment (using high temperature torch). Figure S2. Preparation of the simulated Ag-Cu alloy flake samples. Figure S3. Position of spot analysis and EDS spectrum (Sno corr). Figure S4���S15. Accelerated aging by different solutions. Figure S16. Accelerated aging by 0.1 M Fe(NO3)3 + 1.0 M AgNO3 for 27 days. Figure S17���S33. Load-displacement curves (P-x) of different samples obtained by three-point bending tests (black dotted lines: no corr-Sno corr, the original simulated Ag-Cu alloy samples; corr-Scorr, the corroded simulated Ag-Cu alloy samples). Figure S34. The diamond-shaped indentation left on the surface of the sample after microhardness tests. Figure S35. The microstructure of the samples after thermal treatments. Figure S36. Position of spot analysis and EDS spectrum (S850). Figure S37. Position of spot analysis and EDS spectrum (S550). Figure S38. Position of spot analysis and EDS spectrum (Sno air 850). Figure S39. Schematic diagram of simple-bending experiment. Table S1���S17. Calculation results of ��bb, Eb, and HV of different samples. Table S18. MATLAB code of P-f curve extrapolation.