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- W4292371330 abstract "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." @default.
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- W4292371330 date "2022-08-19" @default.
- W4292371330 modified "2023-09-27" @default.
- W4292371330 title "Towards a machine-readable literature: finding relevant papers based on an uploaded powder diffraction pattern" @default.
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- W4292371330 doi "https://doi.org/10.1107/s2053273322007483" @default.
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