Evaluating large language models for drafting emergency department encounter summaries is a research paper published in PLOS Digital Health (2025). On theSindex it has a DataRank of 0.842. It has been cited 26 times, with 26 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.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.494
From this paper's citation signal
Citation Network Contribution
0.347
From 11 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 26 citers.
NICHD NIH HHS
Grant: K23 HD110716
National Institutes of Health
Grant: 5K23HD110716-02
Accurate and Reliable Diagnostics for Injured Children: Machine Learning for Ultrasound
FWCI
47.60
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals