Gamma-ray burst data strongly favour the three-parameter fundamental plane (Dainotti) correlation over the two-parameter one is a dataset published in Monthly Notices of the Royal Astronomical Society (2022). On theSindex it has a DataRank of 0.917, placing it in the top 22.1% of the data-sharing corpus. It has been cited 48 times, with 27 citing works in its 1-hop citation network.
Ranks in the top 22% for downstream scientific impact
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.584
From this paper's citation signal
Citation Network Contribution
0.333
From 22 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 27 citers.
DOE
Grant: DE-SC0011840
NSF
Grant: CNS-1006860
NSF
Grant: EPS-1006860
NSF
Grant: EPS-0919443
NSF
Grant: ACI-1440548
NSF
Grant: CHE-1726332
NIH
Grant: P20GM113109
National Science Foundation
Grant: 1006860
Prairie Light: Next Generation Networking for Mid-continent Science
National Science Foundation
Grant: 1726332
MRI: Acquisition of a GPU-Enabled Computer Cluster for Molecular Modeling Applications
National Science Foundation
Grant: 0919443
Collaborative Research: EPSCoR RII Track 2 Oklahoma and Kansas: A cyberCommons for Ecological Forecasting
National Science Foundation
Grant: 1440548
CC-IIE Networking Infrastructure: KGEN: Next-generation networking environments for biological and agricultural data-driven research at Kansas State University
National Institutes of Health
Grant: 2P20GM113109-06
Cognitive and Neurobiological Approaches to Plasticity (CNAP) Center Phase 2
Fields of Study
Keywords