Created by Cell Press, Structured Transparent Accessible Reporting (STAR) is a table framework for key resources designed to improve rigor and reproducibility across scientific research. The format ensures researchers report enough information to replicate research results using the same exact key resources. For more information on STAR, please visit their website.
With every submission to our systems, SciScore returns a STAR table (downloadable as a .csv) in addition to our other reports, which is partially completed automatically using information detected in your research. You will most likely need to fill in additional information depending on your research topic as SciScore is currently only trained to detect a limited number of criteria. If SciScore makes substantial mistakes with your manuscript, please contact us to help us learn from our mistakes.
The STAR table reports a reagent or resource name, a source, and an identifier for each key resource essential to an experiment. The following key resource types are listed:
SciScore is a machine learning, text analysis tool and is therefore susceptible to making two types of errors: false positives and false negatives.
False negatives: The most common error occurs when our models fail to detect a sentence that contains a rigor criterion or a resource, such as an antibody. False negatives generally occur either because the sentence is complex or in a less common syntactic pattern. Generally, simple sentences in clear standard English are simpler to process and result in fewer false negatives. If a truly complex sentence structure is required to describe reagents, a table may help not only SciScore but also human readers. If an RRID is detected in a sentence, SciScore will be triggered to take a look at the sentence, which may have been skipped otherwise.
False positives: This type of error occurs when our models falsely detect criteria that is not present. We try to minimize these false positives using several strategies, however, they still occur in roughly 3-5% of cases. If this impacts your SciScore experience, please contact our team and include the sentence where SciScore made the error. SciScore is always trying to learn from its mistakes for improved performance next time around.