{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T20:33:50Z","timestamp":1768077230286,"version":"3.49.0"},"reference-count":91,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T00:00:00Z","timestamp":1754611200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012325","name":"National Office for Philosophy and Social Sciences, Beijing, China","doi-asserted-by":"publisher","award":["23&ZD225 2023"],"award-info":[{"award-number":["23&ZD225 2023"]}],"id":[{"id":"10.13039\/501100012325","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Identifying frontier interdisciplinary domains is essential for tracking scientific evolution and informing strategic research planning. This study proposes a comprehensive framework that integrates (1) semantic disciplinary classification using a large language model (GPT-3.5-Turbo), (2) quantitative metrics for interdisciplinarity (degree and integration strength) and frontierness (novelty, growth, and impact), and (3) trend prediction using time series models, including Transformer, LSTM, GRU, Random Forest, and Linear Regression. The framework systematically captures both structural and temporal dimensions of emerging research fields. Compared to conventional citation-based or topic modeling approaches, it enhances semantic precision, supports multi-label classification, and enables forward-looking forecasts. Empirical validation shows that the Transformer model achieved the highest predictive performance, outperforming other deep learning and baseline models. As an illustrative example, the framework was applied to synthetic biology, which demonstrated high interdisciplinarity, strong novelty, and growing academic influence. These results underscore the field\u2019s strategic position as a frontier interdisciplinary domain. Beyond this case, the proposed framework is generalizable to other domains and provides a scalable, data-driven solution for dynamic monitoring of emerging interdisciplinary areas. It holds promise for applications in science and technology intelligence, research evaluation, and policy support.<\/jats:p>","DOI":"10.3390\/systems13080677","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T15:30:52Z","timestamp":1754667052000},"page":"677","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Identification and Prediction Methods for Frontier Interdisciplinary Fields Integrating Large Language Models"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1565-8222","authenticated-orcid":false,"given":"Yu","family":"Wu","sequence":"first","affiliation":[{"name":"Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7687-1679","authenticated-orcid":false,"given":"Qiao","family":"Lin","sequence":"additional","affiliation":[{"name":"Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinming","family":"Wu","sequence":"additional","affiliation":[{"name":"Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ru","family":"Yao","sequence":"additional","affiliation":[{"name":"Institute of Data Science and Agricultural Economy, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuefu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Klein, J.T. 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