
This deliverable needs to be seen as one item of a classical and logical execution of a machine learning (ML) application. Given availability/ingestion of data, we first perform an exploratory data analysis to get familiar with the data, analyse statistical parameters and distribution, check for completeness, outliers and other characteristics which could be relevant for the choice of the machine learning. This in-depth data analysis is covered by this deliverable D3.1 UC exploratory data analysis
FAIRiCUBE, data analyses
FAIRiCUBE, data analyses
| 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 |
