Aries Systems Corporation

With unintentional errors/under-specification from untrained researchers, sophisticated fraud techniques led by bad actors, and pressure on researchers from the “publish or perish” career advancement culture – maintaining integrity in scholarly publishing has never been more critical and challenging. Fueling the “reproducibility crisis”, poorly controlled or documented studies negatively impact the quality of research and can harm the communities that rely on the integrity of published data – especially for the science and medical field. It is imperative for publications to adhere to strict screening policies during the editorial and peer review process, but it is unrealistic for institutions and publishers to manually replicate all experiments that are submitted for publication. Therefore, publishers rely on qualified Reviewers to analyze the submission and its methods to assess the reproducibility on paper. This can be time-consuming, incur costly demands on resources, and cause delays to publication.

To help Authors and publishers adhere to rigor and transparency criteria for better reproducibility of scientific research, SciCrunch offers an innovative methods review tool for scientific articles. Scanning the methods section(s) of a research paper, SciScore™ detects whether Authors address bias, sample size, sex, blinding, the randomization of subjects, and properly identified key biological resources (i.e., research reagents such as antibodies and organisms). This evaluation produces a score that corresponds to the number of criteria filled compared to the number that was expected, along with a detailed report for actionable improvement suggestions. SciScore leverages reporting standards from MDAR, ARRIVE, CONSORT, AVMA, and NIH and persistent identifiers (PIDs) such as Research Resource Identifiers (RRIDs) to automate the assessment of reproducibility of scientific research at scale.

SciScore is seamlessly integrated with Editorial Manager® (EM), the leading manuscript submission and peer review tracking system, to further streamline this process. Once the Author enters the materials and methods section into EM during submission, an analysis of the article’s content is automatically triggered and sent to SciScore. The generated score and reports are returned to EM and can be made available to Authors, Editors, and Reviewers – delivering an efficient quality check solution directly within the users’ existing workflow.

Through the recent release of SciScore version 3, a new statistics module and Author/Reviewer dashboard are now available! A redesigned report interface features a new summary cover page on how well the article adheres to rigor and transparency guidelines. A new green check icon serves as a convenient indicator if methods are compliant for the given guideline item or when Key Resources are identifiable using a given RRID. Additionally, reports are enhanced with comprehensive explanations are suggestions to help Authors understand the scoring rationale and make improvements. The brand-new AI-based statistics module checks the statistical methods used, guides Authors on expected reporting practices and, reminds Authors and Reviewers to check whether the data tested meets statistical assumptions.

SciCrunch recently announced the successful implementation of structured Key Resource tables for bioRxiv preprints. Funded by the Chan Zuckerberg Initiative (CZI), these standardized tables of reagents will be available universally to search engines, make it more feasible to collect this data from Authors, and support the opportunity for the reported findings to be reproduced.

Generated in just minutes, SciScore reports drive standardized rigor and transparency in scientific and medical research, which often suffers from the reproducibility crisis. Through the power of SciScore, the reproducibility of science is measurable, and Authors, Editors, and Reviewers are empowered to make focused corrections. SciScore is one of the many powerful quality solutions integrated with EM through the Aries ecosystem of best-in-class technologies. To learn more about how to leverage SciScore with Editorial Manager, contact info@sciscore.com or visit scicrunch.com/contact.