Automated Author ProfileAzenor Bideault
Azenor Bideault
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: 0.5 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Values of activation energies collected from previous meta-analyses with the objective of depicting a general overview of the temperature sensitivity of biomass distribution and trophic control in food chains for various consumer-resource systems. We used the meta-analyses from Dell et al 2011, Burnside et al 2014 and Fussmann et al 2014, reporting activation energies for different biological rates and types of organisms. In these studies, activation energies are estimated by fitting the linearized Arrhenius equation to the log transformed biological rates.
Authors
- Azenor Bideault
Values of activation energies collected from previous meta-analyses with the objective of depicting a general overview of the temperature sensitivity of biomass distribution and trophic control in food chains for various consumer-resource systems. We used the meta-analyses from Dell et al 2011, Burnside et al 2014 and Fussmann et al 2014, reporting activation energies for different biological rates and types of organisms. In these studies, activation energies are estimated by fitting the linearized Arrhenius equation to the log transformed biological rates.
Authors
- Azenor Bideault