Research Square is beta testing the new artificial intelligence (AI) based SciScore assessment tool for its preprint platform.
ScisScore will help scientists assess their manuscripts for reproducibility and adherence to rigor standards after uploading their preprints onto Research Square — at no cost during the beta trial.
“As an integrated part of the preprinting process on our platform, SciScore will help authors ensure the science behind their manuscripts is better prepared for peer review,” said Rachel Burley, President of Research Square Company. “We are excited to expand the range of tools and services available to researchers through the Research Square platform and to work with such an innovative partner.”
SciScore scans preprint methods against various research guidelines and rigor criteria known to support the reproducibility of scientific research, including evidence of reagent identifiability, randomization, sample size estimation, and more. SciScore also analyzes sentences for uniquely identifiable research resources, then generates a Methods Completeness Score and report that will help authors improve the rigor and reproducibility of their preprints.
“It’s estimated that 50 percent of the United States’ preclinical research spend in recent years is not reproducible, mainly due to flaws in reference material, unreliable source identification, and similar issues,” said Anita Bandrowski, Founder and CEO of SciCrunch, which produces SciScore. “Our solution helps flag cell line contamination and other issues for authors at the preprint phase, before they’re submitted to journals.”
Authors uploading their manuscripts to Research Square can opt to receive the SciScore-based Methods Completeness Score and report at no cost through November 1, 2020.
