
This dataset is part of the Supplemental Material of "Tracking garnet dissolution kinetics in 3D using deep learning grain shape classification" by Hartmeier et al. (2023). Garnet grain 3D models extracted from a micro-computed tomography scan. "ZS2102raw" are numpy arrays (.npy-files) holding a 3D model of garnet grains. Additional information; centroid position, volume in voxels and volume of fitted convex hulls ; is stored in seperate files. "ZS2102_labelled" holds the same data set but all garnets are catergorised in to different shape based classes.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
