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Dataset . 2020
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Dataset . 2020
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Dataset . 2020
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Claim

Silicon-29 NMR Experimental Datasets used in Statistical Learning of NMR tensors from 2D Isotropic/Anisotropic Correlation Nuclear Magnetic Resonance Spectra

Research datakeyboard_double_arrow_right Dataset 28 Jul 2020Publisher:Zenodo
Authors: Srivastava, Deepansh J.; Grandinetti, Philip J.;

doi: 10.5281/zenodo.3964531 , 10.5281/zenodo.4015100 , 10.5281/zenodo.3964530

Silicon-29 NMR Experimental Datasets used in Statistical Learning of NMR tensors from 2D Isotropic/Anisotropic Correlation Nuclear Magnetic Resonance Spectra

Abstract

Processed silicon-29 Magic-Angle Flipping and Magic-Angle Turning Nuclear Magnetic Resonance used as input to the smooth-LASSO linear inversion algorithm described in submitted manuscript "Statistical Learning of NMR tensors from 2D Isotropic/Anisotropic Correlation Nuclear Magnetic Resonance Spectra", by Srivastava and Grandinetti. Details of the csdf dataset format are given in PLOS ONE, 15(1): e0225953 (2020), "Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data," D. Srivastava, T. Vosegaard, D. Massiot, and P.J. Grandinetti. The data within csdf files can be accessed with the Python package csdmpy, or other CSDM-compliant software.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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