Developing Quantitative Structure–Activity Relationship (QSAR) Models for Water Contaminants’ Activities/Properties by Fine-Tuning GPT-3 Models-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Developing Quantitative Structure–Activity Relationship (QSAR) Models for Water Contaminants’ Activities/Properties by Fine-Tuning GPT-3 Models

Published:2023-09-20 Issue:10 Volume:10 Page:872-877
ISSN:2328-8930
Container-title:Environmental Science & Technology Letters
language:en
Short-container-title:Environ. Sci. Technol. Lett.

Author:

Zhong Shifa¹^ORCID,Guan Xiaohong¹^ORCID

Affiliation:

1. Department of Environmental Science, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, P. R. China

Funder

Science and Technology Commission of Shanghai Municipality

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,Water Science and Technology,Ecology,Environmental Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.estlett.3c00599

Reference27 articles.

1. Machine Learning: New Ideas and Tools in Environmental Science and Engineering

2. Rapid and Accurate Prediction of pKa Values of C–H Acids Using Graph Convolutional Neural Networks

3. MoleculeNet: a benchmark for molecular machine learning

4. A deep neural network combined with molecular fingerprints (DNN-MF) to develop predictive models for hydroxyl radical rate constants of water contaminants

5. Shedding light on “Black Box” machine learning models for predicting the reactivity of HO radicals toward organic compounds

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Large Language Models for Inorganic Synthesis Predictions;Journal of the American Chemical Society;2024-07-11

2. Machine learning framework for predicting cytotoxicity and identifying toxicity drivers of disinfection byproducts;Journal of Hazardous Materials;2024-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3