Democratizing machine learning in chemistry with community-engaged test sets

Machine learning (ML) is increasingly central to chemical discovery, yet most efforts remain confined to distributed and isolated research groups, limiting external validation and community engagement.

Institutions

Publication Details

Journal
Digital Discovery
Published
2025-11-19
DOI
https://doi.org/10.1039/d5dd00424a
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Democratizing machine learning in chemistry with community-engaged test sets

1 citations
Digital Discovery
Machine Learning in Materials Science
0.52
article

Democratizing machine learning in chemistry with community-engaged test sets

article en
1 citations

Abstract

Machine learning (ML) is increasingly central to chemical discovery, yet most efforts remain confined to distributed and isolated research groups, limiting external validation and community engagement.

Digital DiscoveryVol. 5(1)
University of Illinois Urbana-Champaign (US), Illinois College (US)
National Science Foundation
Openalex Percentile: Top 29%
Machine Learning in Materials Science
0.52
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Democratizing machine learning in chemistry with community-engaged test sets · Digital Discovery (2025) | TGRS Research Map | TGRS