Automated Author ProfileA. Murphy, Bailey
A. Murphy, Bailey
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: 0.6 (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 descriptions of variables used in a Geographically Weighted Regression (GWR) model to model spatial relationships between forest productivity with climate, management, topography, and soil. First, the data for the GWR model were collected from different sources such as USGS, SSURGO, PRISM, and ED2-derived output. The GWR4 software was then used to estimate the local coefficients of landscapes across study areas.
Authors
- Karimi, Hazhir ;
- Binford, Michael ;
- Kleindl, William ;
- Starr, Gregory ;
- A. Murphy, Bailey ;
- R. Desai, Ankur ;
- Fu, Chiung-Shiuan ;
- C. Dietze, Michael
This dataset contains the descriptions of variables used in a Geographically Weighted Regression (GWR) model to model spatial relationships between forest productivity with climate, management, topography, and soil. First, the data for the GWR model were collected from different sources such as USGS, SSURGO, PRISM, and ED2-derived output. The GWR4 software was then used to estimate the local coefficients of landscapes across study areas.
Authors
- Karimi, Hazhir ;
- Binford, Michael ;
- Kleindl, William ;
- Starr, Gregory ;
- A. Murphy, Bailey ;
- R. Desai, Ankur ;
- Fu, Chiung-Shiuan ;
- C. Dietze, Michael