Fine-Grained Forecasting of COVID-19 Trends at the County Level in the United States is a research paper published in medRxiv (2024). On theSindex it has a DataRank of 0.230. It has been cited 3 times, with 3 citing works in its 1-hop citation network.
Scored on demand from live citation data
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.
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Base Score Contribution
0.208
From this paper's citation signal
Citation Network Contribution
0.0219
From 1 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 3 citers.
National Institutes of Health
Grant: 1R35GM133725-01
Unraveling subcellular heterogeneity of molecular coordination by machine learning
National Institutes of Health
Grant: 5R01GM130668-05
Development of an Open-Source and Data-Driven Modeling Platform to Monitor and Forecast Disease Activity
NIGMS NIH HHS
Grant: R01 GM130668
NIGMS NIH HHS
Grant: R35 GM133725
Fields of Study
Keywords
Sustainable Development Goals