An efficient and accurate distributed learning algorithm for modeling multi-site zero-inflated count outcomes is a research paper published in Scientific Reports (2021). On theSindex it has a DataRank of 0.457. It has been cited 20 times.
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.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.457
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Institutes of Health
Grant: 1R01LM012607
National Institutes of Health
Grant: R01CA246418
Pennsylvania Department of Health
Grant: 4100072543
NIA NIH HHS
Grant: R01 AG073435
NIAID NIH HHS
Grant: R01 AI130460
NLM NIH HHS
Grant: R01 LM012607
National Institutes of Health
Grant: 5R01LM012607-03
A General Framework to Account for Outcome Reporting Bias in Systematic Reviews
National Institutes of Health
Grant: 5R01AG073435-04
TRiPOD: Toward Reusable Phenotypes in Observational Data for AD/ADRD - managing definitions and correcting bias
National Institutes of Health
Grant: 5R01LM013039-02
HealthyMe/MiSalud Smartphone Application: Identifying Mechanisms to Engage African Americans and Hispanics in Personal Health Libraries
National Institutes of Health
Grant: 5R01CA246418-04
The benefits and harms of lung cancer screening in Florida
National Institutes of Health
Grant: 1R01AI130460-01
Dynamic learning for post-vaccine event prediction using temporal information in VAERS
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals