Automated Author ProfileAugustijn, Eva
0009-0008-4947-1926
Augustijn, Eva
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The analysed data and full scripts for the ECSA determination, onset potential determination, micro-CT data analysis and DTW distance calculation used in the paper 'Novel Miniaturised Microbial Electrosynthesis Reactor: A Study on Replicability'.Python version 3.10.13 with packages numpy, pandas, os, scipy.optimize, scipy.stats, sklearn.metrics, dtaidistance, math, skfda, kneed, matplotlib.pyplot are required to run the .py files. Ensure all packages are installed before running the scripts. Data files required to run the code (.xlsx and .csv format) are included in the relevant folders.
Authors
- Zegers, Marika ;
- Augustijn, Eva ;
- Jongbloed, Geurt ;
- Jourdin, Ludovic
The analysed data and full scripts for the ECSA determination, onset potential determination, micro-CT data analysis and DTW distance calculation used in the paper 'Novel Miniaturised Microbial Electrosynthesis Reactor: A Study on Replicability'.Python version 3.10.13 with packages numpy, pandas, os, scipy.optimize, scipy.stats, sklearn.metrics, dtaidistance, math, skfda, kneed, matplotlib.pyplot are required to run the .py files. Ensure all packages are installed before running the scripts. Data files required to run the code (.xlsx and .csv format) are included in the relevant folders.
Authors
- Zegers, Marika ;
- Augustijn, Eva ;
- Jongbloed, Geurt ;
- Jourdin, Ludovic