Author Archives: Kan Hatakeyama-Sato

Using GPT-4 in parameter selection of polymer informatics: improving predictive accuracy amidst data scarcity and ‘Ugly Duckling’ dilemma

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Digital Discovery, 2023, 2,1548-1557
DOI: 10.1039/D3DD00138E, Paper
Open Access Open Access
Creative Commons Licence  This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.
Kan Hatakeyama-Sato, Seigo Watanabe, Naoki Yamane, Yasuhiko Igarashi, Kenichi Oyaizu
Data scarcity in materials informatics hinders structure–property relationships. Using GPT-4 can address challenges, improving predictions like polymer refractive indices.
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