Automated Author ProfileSartori, Giuseppe
University of Padua
Sartori, Giuseppe
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: 2.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This repository contains the dataset associated with the original paper "Investigating the truthfulness of autobiographical events through mouse dynamics”, by M. Monaro, A. Guiotto, G. Sartori. Data are organized as follows:- the dataset used by the authors to perform statistical analysis (ANOVAs) (.xls)- the training sets used by the authors to train and validate ML models (.arff)- the test sets used by the authors to test the ML models (.arff)The "Data dictionary" file contains the description of the variables in each data file..arff files can be directly run in WEKA software 3.9.The "Details on ML classifiers parameters" file contains the algorithm parameters used to tun ML classifiers.
Authors
- Monaro, Merylin ;
- Guiotto, Alessandra ;
- Sartori, Giuseppe
This repository contains the dataset associated with the original paper "Investigating the truthfulness of autobiographical events through mouse dynamics”, by M. Monaro, A. Guiotto, G. Sartori. Data are organized as follows:- the dataset used by the authors to perform statistical analysis (ANOVAs) (.xls)- the training sets used by the authors to train and validate ML models (.arff)- the test sets used by the authors to test the ML models (.arff)The "Data dictionary" file contains the description of the variables in each data file..arff files can be directly run in WEKA software 3.9.The "Details on ML classifiers parameters" file contains the algorithm parameters used to tun ML classifiers.
Authors
- Monaro, Merylin ;
- Guiotto, Alessandra ;
- Sartori, Giuseppe