Key Highlights:
- DeSci Labs has released a new mathematical model scores feature which is an objective measure of novelty for scientific work, now available to the public.
- The release of these novelty scores for over 250 million scientific articles by DeSci Labs means there is now an objective, automated measurement of one of the core parts of the peer review process.
- Users can search for authors, topics, journals, or institutions and identify their novelty scores, including works by past Nobel Prize winners and the newest preprints from all fields of science.
DeSci
As part of its commitment to improving transparency in scientific publishing, Open Access science company DeSci Labs has released its new novelty scores feature. This is the first time an objective measure of novelty for scientific work is available to the public, which will help provide incentives for novel work to be published and funded, helping to accelerate scientific progress.
A mathematical model that provides an objective measure of novelty which has been trained on over 55 million articles via Open Alex and made publicly available for over 250 million articles. The measurement is based on an algorithm developed in a paper published in Nature Communications by professors James Evans from the University of Chicago and Feng Shi from George Washington University.
Discovering novel insights that expand human knowledge is one of the most important purposes of scientific research. As a result, evaluating the novelty of scientific manuscripts and grant applications takes centre stage in the scientific peer review process. The primary reason work is rejected by editors of high-impact journals or funding agencies is because referees think it is not novel enough. However, the current peer review process is subjective, slow, labour-intensive, and prone to bias and inaccuracy. In many cases, referees disagree on whether a particular contribution or idea is novel.
The release of these novelty scores for over 250 million scientific articles by DeSci Labs means there is now an objective, automated measurement of one of the core parts of the peer review process.
“We now have an algorithm that can carry out an important part of the evaluation function in science much quicker and often better than the subjective judgement human experts,” explained professor Philipp Koellinger, CEO and co-founder of DeSci Labs. “Our novelty scores show a strong, positive relationship with the future citation counts of an article, making this new metric both interesting and practically useful.”
“We wanted a measure of surprise that captured the native complexity of the combinations of conceptual elements, and of sources, rather than summing over pairwise combinations,” added professor James Evans. “I believe that novel research in science and technology is important and should be appropriately measured relative to the available data.”
DeSci Publish’s new feature allows users to search and explore novelty scores for the vast majority of the available scientific literature, including works by past Nobel Prize winners and the newest preprints from all fields of science. Users can search for authors, topics, journals, or institutions and create ad-hoc novelty score rankings.
Scientists will soon be able to see novelty scores for every version of their manuscript they upload on DeSci Publish; while soon-to-be released premium features will allow users to calculate novelty scores for any scientific manuscript or grant application they care about.