Consistency and reliability of automated language measures across expressive language samples in autism is a dataset published in Autism Research (2023). On theSindex it has a DataRank of 0.459, placing it in the top 41.3% of the data-sharing corpus. It has been cited 12 times, with 9 citing works in its 1-hop citation network.
Ranks in the top 41% for downstream scientific impact
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
0.385
From this paper's citation signal
Citation Network Contribution
0.0745
From 3 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 9 citers.
National Institutes of Health
Grant: UL1TR001860
National Institutes of Health
Grant: P50HD103526
National Institutes of Health
Grant: R01HD074346
National Institutes of Health
Grant: R01DC012033
Simons Foundation
Grant: SFARI 383668
NCATS NIH HHS
Grant: UL1 TR002369
National Institutes of Health
Grant: 3R01HD074346-03S1
Expressive Language Sampling as an Outcome Measure
National Institutes of Health
Grant: 5P50HD103526-03
MIND Institute Intellectual and Developmental Disabilities Research Center
National Institutes of Health
Grant: 5UL1TR001860-10
UC Davis Clinical and Translational Science Center
National Institutes of Health
Grant: 5R01DC012033-05
Computational characterization of language use in autism spectrum disorder
FWCI
1.58
Citation Percentile
0.8%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals