Automated Organization ProfileLantmännen Lantbruk (Sweden)
Lantmännen Lantbruk (Sweden)
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization'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 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Additional file 1: Table S1. Spearman’s correlation analysis between yellow rust disease scores and model predictor variables derived from high-throughput phenotyping (HTPP) data collected at two dates under field conditions.
Authors
- Koc, Alexander ;
- Odilbekov, Firuz ;
- Alamrani, Marwan ;
- Henriksson, Tina ;
- Chawade, Aakash
Additional file 1: Table S1. Spearman’s correlation analysis between yellow rust disease scores and model predictor variables derived from high-throughput phenotyping (HTPP) data collected at two dates under field conditions.
Authors
- Koc, Alexander ;
- Odilbekov, Firuz ;
- Alamrani, Marwan ;
- Henriksson, Tina ;
- Chawade, Aakash
Additional file 2: Table S2. Full ranking of high-throughput phenotyping features of based on results of recursive feature elimination (RFE).
Authors
- Koc, Alexander ;
- Odilbekov, Firuz ;
- Alamrani, Marwan ;
- Henriksson, Tina ;
- Chawade, Aakash
Additional file 2: Table S2. Full ranking of high-throughput phenotyping features of based on results of recursive feature elimination (RFE).
Authors
- Koc, Alexander ;
- Odilbekov, Firuz ;
- Alamrani, Marwan ;
- Henriksson, Tina ;
- Chawade, Aakash