Closing the gap between open source and commercial large language models for medical evidence summarization is a research paper published in npj Digital Medicine (2024). On theSindex it has a DataRank of 0.648. It has been cited 74 times.
Scored on demand from live citation data
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.
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Base Score Contribution
0.648
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 →U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine
Grant: R01LM014344
U.S. Department of Health & Human Services | National Institutes of Health
Grant: UL1TR001873
NHGRI NIH HHS
Grant: R01 HG012655
NCATS NIH HHS
Grant: UL1 TR002384
NLM NIH HHS
Grant: T15 LM007079
NLM NIH HHS
Grant: R01 LM009886
National Institutes of Health
Grant: 3UL1TR001873-07S1
Clinical and Translational Science Award
National Institutes of Health
Grant: 5R01LM014344-03
ClinEX - Clinical Evidence Extraction, Representation, and Appraisal
National Institutes of Health
Grant: 5T15LM007079-29
Training in Biomedical Informatics at Columbia University
National Institutes of Health
Grant: 5R01LM009886-02
Bridging the Semantic Gap Between Research Eligibility Criteria and Clinical Data
National Institutes of Health
Grant: 5UL1TR002384-03
Clinical and Translational Science Center
National Institutes of Health
Grant: 5R01HG012655-03
RESCUE: Rare Disease Detection and Escalation Support via a Learning Health System
FWCI
17.66
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords