Scratch-AID, a deep learning-based system for automatic detection of mouse scratching behavior with high accuracy is a research paper published in eLife (2022). On theSindex it has a DataRank of 0.555. It has been cited 15 times, with 12 citing works in its 1-hop citation network.
Scored on demand from live citation data
Repositories this paper deposited data in (declared in PubMed).
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
0.416
From this paper's citation signal
Citation Network Contribution
0.139
From 8 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 12 citers.
National Science Foundation
Grant: DMS-1854770
National Institutes of Health
Grant: R01 NS083702
National Institutes of Health
Grant: R34 NS118411
National Institutes of Health
Grant: 1R34NS118411-01
Developing A Mouse Chronic Pain Scale by 3D Imaging and Measurement of Mouse Spontaneous Behaviors
National Institutes of Health
Grant: 3R01NS083702-03S1
Molecular mechanisms in controlling development of touch-sensing neurons
National Science Foundation
Grant: 1854770
Collaborative Research: Computational Topology and Categorification of Cancer Genomic Data: Theory and Algorithms
FWCI
2.26
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals