🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Extracting Structural Information from Physicochemical Property Measurements Using Machine Learning─A New Approach for Structure Elucidation in Non-targeted Analysis

Environmental Science & Technology(2023)10.1021/acs.est.3c03003Source: DataRank Database

Extracting Structural Information from Physicochemical Property Measurements Using Machine Learning─A New Approach for Structure Elucidation in Non-targeted Analysis is a research paper published in Environmental Science & Technology (2023). On theSindex it has a DataRank of 0. It has been cited 9 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access9 citations

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (15 grants)OA: hybridTopics (17)IDs (PubMed)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (8)

Christopher L. Brueck ORCID,Carsten Prasse ORCID,Dimitra A. Lambropoulou ORCID,Lelouda-Athanasia Koronaiou ORCID,Miaomiao Wang ORCID

Live enrichment

PubMed:19910364

National Institute of Environmental Health Sciences

Grant: K99ES032892

National Institute of Environmental Health Sciences

Grant: P01ES022841

National Institute of Environmental Health Sciences

Grant: P30ES030284

National Institute of Environmental Health Sciences

Grant: R00ES032892

National Institute of Environmental Health Sciences

Grant: R01ES027051

National Institute of Environmental Health Sciences

Grant: UG3OD023272

National Institute of Environmental Health Sciences

Grant: UH3OD023272

U.S. Environmental Protection Agency

Grant: RD83543301

U.S. Environmental Protection Agency

Grant: RD83564301

National Institutes of Health

Grant: 1K99ES032892-01

Non-target analysis of maternal and cord blood samples: Advancing computational tools and discovering novel chemicals

National Institutes of Health

Grant: 3P01ES022841-03S2

The UCSF Pregnancy Exposures to Environmental Chemicals (PEEC) Childrens Center

National Institutes of Health

Grant: 1P30ES030284-01A1

UCSF Environmental Research and Translation for Health Center (EaRTH Center)

National Institutes of Health

Grant: 3UH3OD023272-06S2

Cumulative Effects of Prenatal Stress and Chemical Exposures on Child Development

National Institutes of Health

Grant: 5UG3OD023272-09

The Illinois Kids Development Study ECHO Pregnancy and Pediatric Cohort

National Institutes of Health

Grant: 5R01ES027051-02

Discovery of novel environmental chemicals in a diverse population of maternal-infant pairs

hybridLicense: cc-by

publisherhttps://pubs.acs.org/doi/pdf/10.1021/acs.est.3c03003

repositoryhttps://escholarship.org/content/qt1sk5752d/qt1sk5752d.pdf?t=s2tguf

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10569036/pdf/es3c03003.pdf

https://doi.org/10.1021/acs.est.3c03003

https://pubmed.ncbi.nlm.nih.gov/37746919

Fields of Study

01 natural sciences0104 chemical sciences

Keywords

ChromatographyLiquidstructure elucidationWaterphysicochemical properties540non-targeted analysisMass SpectrometryAnalytical Chemistrymachine learningChemical SciencesMachine Learning and Artificial IntelligenceSolventsEnvironmental SciencesChromatography, Liquid