Automated Author ProfileVivek, Kavyesh
Imperial College London
Vivek, Kavyesh
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: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset contains the research data from two studies (Study 1 with members of the general public, N = 99; Study 2 with medical students, N = 69) reported in the following conference paper:Rago, A., Pálfi, B., Sukpanichnant, P., Vivek, K., Nabli, H., Kostopoulou, O., Kinross, J., & Toni, F. (Accepted). Exploring the Effect of Explanation Content and Format on User Comprehension and Trust in Healthcare. 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025). Preprint available at https://arxiv.org/abs/2408.17401.All data are fully anonymized and comply with institutional ethical guidelines. For each study, two datasets are provided: (1) the processed and cleaned experimental data in long format by hypothetical scenario (test), and (2) the remaining research data in wide format (pre-test). A README file is included, providing detailed information about all measured variables.
Authors
- Rago, Antonio ;
- Pálfi, Bence ;
- Sukpanichnant, Purin ;
- Vivek, Kavyesh ;
- Nabli, Hannibal ;
- Kostopoulou, Olga ;
- Kinross, James ;
- Toni, Francesca
This dataset contains the research data from two studies (Study 1 with members of the general public, N = 99; Study 2 with medical students, N = 69) reported in the following conference paper:Rago, A., Pálfi, B., Sukpanichnant, P., Vivek, K., Nabli, H., Kostopoulou, O., Kinross, J., & Toni, F. (Accepted). Exploring the Effect of Explanation Content and Format on User Comprehension and Trust in Healthcare. 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025). Preprint available at https://arxiv.org/abs/2408.17401.All data are fully anonymized and comply with institutional ethical guidelines. For each study, two datasets are provided: (1) the processed and cleaned experimental data in long format by hypothetical scenario (test), and (2) the remaining research data in wide format (pre-test). A README file is included, providing detailed information about all measured variables.
Authors
- Rago, Antonio ;
- Pálfi, Bence ;
- Sukpanichnant, Purin ;
- Vivek, Kavyesh ;
- Nabli, Hannibal ;
- Kostopoulou, Olga ;
- Kinross, James ;
- Toni, Francesca