研究论文开放获取
Orchestrating explainable AI, ChatGPT, and human expertise: a framework for extracting polymer design guidelines
Yin Kan Phua, Nana Terasoba, Manabu Tanaka, Tsuyohiko Fujigaya, Koichiro Kato
Kyushu University Tokyo Metropolitan University Research Institute for Information Technology, Kyushu University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
摘要 · 完整
Orchestrating XAI, ChatGPT, and expert knowledge to extract actionable and chemically intuitive guidelines for designing high-performance functional polymers.
逐年被引趋势
暂无年度引用数据
关键指标
0
被引次数 · OpenAlex
0.00
领域内被引倍数
同类平均 = 1
同类平均 = 1
前 84%
引用位次
同领域 · 同年份 · 同类型
同领域 · 同年份 · 同类型
129
参考文献
Google Scholar 与 OpenAlex 的被引统计范围不同，数值存在差异属正常。
AI 辅助阅读
依据：摘要
论文问答
当前基于摘要回答
可就本文提问；依据不足时会说明。
学术脉络
学科主题
材料 / 化学Machine Learning in Materials Science
Explainable Artificial Intelligence (XAI) · Artificial Intelligence Applications
参考文献 129
A mini-review on anion exchange membranes for fuel cell applications: Stability issue and addressing strategies
被引 316Jie Cheng, Gaohong He, Fengxiang Zhang · International Journal of Hydrogen Energy · 2015
Anion exchange membranes based on carbazole-containing polyolefin for direct methanol fuel cells
被引 56Ao Nan Lai, Ke Chao Zhou, Yizhi Zhuo · Journal of Membrane Science · 2015
Prediction of nanoparticle transport behavior from physicochemical properties: machine learning provides insights to guide the next generation of transport models
被引 58Eli Goldberg, Martin Scheringer, Thomas Daniel Bucheli · Environmental Science Nano · 2015
此处列出前 3 条
引用本文 -
暂无引用本文的记录