How to stop worrying and love multiple citation experimental data

How to stop worrying and love multiple citation experimental data Full article

Journal

Mendeleev Communications
ISSN: 1364-551X , E-ISSN: 0959-9436

Output data

Year: 2025, Volume: 35, Number: 2, Pages: 224-227 Pages count : 4 DOI: 10.71267/mencom.7710

Authors

Timofeev Yaroslav Vladislavovich ^1,2 , Mrasov Amir M. ^1,2 , Panova Maria V ² , Novikov Fedor Nikolaevich ² , Svitanko Igor ²

Affiliations

1	Department of Chemistry, M. V. Lomonosov Moscow State University, 119991 Moscow, Russian Federation
2	N. D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, 119991 Moscow, Russian Federation

Numerous public databases now collect and disseminate biological activity data from literature and patents, forming the basis for chemogenomics and novel scoring functions. However, data quality is often compromised due to multiple citations of values across different studies with varying protocols. To address this issue, we used the XGBoost model in combination with a BERT-based NLP approach and a distance-based out-of-distribution (OOD) data detection method to enhance classification accuracy and exclude review articles.

Timofeev Y.V. , Mrasov A.M. , Panova M.V. , Novikov F.N. , Svitanko I.
How to stop worrying and love multiple citation experimental data
Mendeleev Communications. 2025. V.35. N2. P.224-227. DOI: 10.71267/mencom.7710 WOS Scopus OpenAlex

Web of science:	WOS:001506165900015
Scopus:	2-s2.0-105007460397
OpenAlex:	W4407709724

DB	Citing
OpenAlex	Нет цитирований
Scopus	Нет цитирований