Tootfinder

@… I wouldn’t have any issues making the paper available, but I also need to report the publication to the SNSF, and then it becomes clear that it’s not compliant (in fact, the type of license is available via Crossref and automatically checked).

@… I wouldn’t have any issues making the paper available, but I also need to report the publication to the SNSF, and then it becomes clear that it’s not compliant (in fact, the type of license is available via Crossref and automatically checked).

PreprintToPaper dataset: connecting bioRxiv preprints with journal publications
Fidan Badalova, Julian Sienkiewicz, Philipp Mayr
https://arxiv.org/abs/2510.01783 https://…

PreprintToPaper dataset: connecting bioRxiv preprints with journal publications
The PreprintToPaper dataset connects bioRxiv preprints with their corresponding journal publications, enabling large-scale analysis of the preprint-to-publication process. It comprises metadata for 145,517 preprints from two periods, 2016-2018 (pre-pandemic) and 2020-2022 (pandemic), retrieved via the bioRxiv and Crossref APIs. Each record includes bibliographic information such as titles, abstracts, authors, institutions, submission dates, licenses, and subject categories, alongside enriched p…

A Living Review Pipeline for AI/ML Applications in Accelerator Physics
Adnan Ghribi
https://arxiv.org/abs/2510.09376 https://arxiv.org/pdf/2510.09376

A Living Review Pipeline for AI/ML Applications in Accelerator Physics
We present an open-source pipeline for generating a \emph{living review} of artificial intelligence (AI) and machine learning (ML) applications in accelerator physics and technologies. Traditional review articles provide static snapshots that are quickly outdated by the rapid pace of research. The presented system automatically harvests publications from multiple bibliographic sources (arXiv, InspireHEP, HAL, OpenAlex, Crossref, and Springer), deduplicates entries, applies semantic filtering to…