A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay is a dataset published in Surgical Innovation (2022). On theSindex it has a DataRank of 0.410, placing it in the top 44.9% of the data-sharing corpus. It has been cited 8 times, with 8 citing works in its 1-hop citation network.
Ranks in the top 45% for downstream scientific impact
Linked data & code
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
0.330
From this paper's citation signal
Citation Network Contribution
0.0807
From 5 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 8 citers.
NIDDK NIH HHS
Grant: K23 DK124515
AHRQ HHS
Grant: R18 HS026640
AHRQ HHS
Grant: R01 HS027793
NHLBI NIH HHS
Grant: R21 HL129028
Patient-Centered Outcomes Research Institute
Grant: CE-12-11-4489
AHRQ HHS
Grant: R01 HS024547
FWCI
1.28
Citation Percentile
0.8%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals