Answers are grounded in this paper and cite their sources.
A prototype application for machine-readable literature is investigated. The program is called pyDataRecognition and serves as an example of a data-driven literature search, where the literature search query is an experimental data set provided by the user. The user uploads a powder pattern together with the radiation wavelength. The program compares the user data to a database of existing powder patterns associated with published papers and produces a rank ordered according to their similarity score. The program returns the digital object identifier and full reference of top-ranked papers together with a stack plot of the user data alongside the top-five database entries. The paper describes the approach and explores successes and challenges.
No takes yet. Share an insight, caveat, or question.
Özer et al. (2022) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: