{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T05:09:54Z","timestamp":1738645794003,"version":"3.35.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T00:00:00Z","timestamp":1738540800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T00:00:00Z","timestamp":1738540800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Intell Syst"],"DOI":"10.1007\/s44196-025-00738-2","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T09:50:53Z","timestamp":1738576253000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hyperbolic Graph Convolutional Network Relation Extraction Model Combining Dependency Syntax and Contrastive Learning"],"prefix":"10.1007","volume":"18","author":[{"given":"Jinzhe","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,3]]},"reference":[{"key":"738_CR1","doi-asserted-by":"publisher","unstructured":"Tian, Y., Chen, G., Song, Y., Wan, X.: Dependency-driven relation extraction with attentive graph convolutional networks. In: Zong, C., Xia, F., Li, W., Navigli, R. (eds.) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 4458\u20134471. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.344","DOI":"10.18653\/v1\/2021.acl-long.344"},{"key":"738_CR2","doi-asserted-by":"publisher","unstructured":"Guo, Z., Zhang, Y., Lu, W.: Attention guided graph convolutional networks for relation extraction. In: Korhonen, A., Traum, D., M\u00e0rquez, L. (eds.) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 241\u2013251. Association for Computational Linguistics, Florence, Italy (2019). doi: https:\/\/doi.org\/10.18653\/v1\/P19-1024","DOI":"10.18653\/v1\/P19-1024"},{"key":"738_CR3","doi-asserted-by":"publisher","unstructured":"Yu, B., Mengge, X., Zhang, Z., Liu, T., Yubin, W., Wang, B.: Learning to prune dependency trees with rethinking for neural relation extraction. In: Scott, D., Bel, N., Zong, C. (eds.) Proceedings of the 28th International Conference on Computational Linguistics, pp. 3842\u20133852. International Committee on Computational Linguistics, Barcelona, Spain (Online) (2020). https:\/\/doi.org\/10.18653\/v1\/2020.coling-main.341","DOI":"10.18653\/v1\/2020.coling-main.341"},{"key":"738_CR4","doi-asserted-by":"crossref","unstructured":"Tjong Kim\u00a0Sang, E.F., De\u00a0Meulder, F.: Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition. In: Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003, pp. 142\u2013147 (2003)","DOI":"10.3115\/1119176.1119195"},{"key":"738_CR5","doi-asserted-by":"publisher","unstructured":"Zelenko, D., Aone, C., Richardella, A.: Kernel methods for relation extraction. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP 2002), pp. 71\u201378. Association for Computational Linguistics (2002). https:\/\/doi.org\/10.3115\/1118693.1118703","DOI":"10.3115\/1118693.1118703"},{"issue":"4","key":"738_CR6","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.12263\/DZXB.20221176","volume":"51","author":"Z Yang-sen","year":"2023","unstructured":"Yang-sen, Z.: Joint extraction of entities and relations based on deep learning: a survey. Acta Electron. Sin. 51(4), 1093\u20131116 (2023). https:\/\/doi.org\/10.12263\/DZXB.20221176","journal-title":"Acta Electron. Sin."},{"key":"738_CR7","doi-asserted-by":"publisher","unstructured":"Miwa, M., Bansal, M.: End-to-end relation extraction using LSTMs on sequences and tree structures. In: Erk, K., Smith, N.A. (eds.) Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1105\u20131116. Association for Computational Linguistics, Berlin, Germany (2016). https:\/\/doi.org\/10.18653\/v1\/P16-1105","DOI":"10.18653\/v1\/P16-1105"},{"key":"738_CR8","unstructured":"Zeng, D., Liu, K., Lai, S., Zhou, G., Zhao, J.: Relation classification via convolutional deep neural network. In: Tsujii, J., Hajic, J. (eds.) Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, pp. 2335\u20132344. Dublin City University and Association for Computational Linguistics, Dublin, Ireland (2014)"},{"key":"738_CR9","unstructured":"Zhang, S., Zheng, D., Hu, X., Yang, M.: Bidirectional long short-term memory networks for relation classification. In: Zhao, H. (ed.) Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation, Shanghai, China, pp. 73\u201378 (2015)"},{"key":"738_CR10","doi-asserted-by":"crossref","unstructured":"Sun, K., Zhang, R., Mao, Y., Mensah, S., Liu, X.: Relation extraction with convolutional network over learnable syntax-transport graph. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 8928\u20138935 (2020)","DOI":"10.1609\/aaai.v34i05.6423"},{"key":"738_CR11","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. In: International Conference on Learning Representations (2017)"},{"key":"738_CR12","doi-asserted-by":"publisher","unstructured":"Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: Burstein, J., Doran, C., Solorio, T. (eds.) Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186. Association for Computational Linguistics, Minneapolis, Minnesota (2019). https:\/\/doi.org\/10.18653\/v1\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"738_CR13","doi-asserted-by":"publisher","unstructured":"Li, B., Zhou, H., He, J., Wang, M., Yang, Y., Li, L.: On the sentence embeddings from pre-trained language models. In: Webber, B., Cohn, T., He, Y., Liu, Y. (eds.) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 9119\u20139130. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.733","DOI":"10.18653\/v1\/2020.emnlp-main.733"},{"key":"738_CR14","doi-asserted-by":"publisher","unstructured":"Yan, Y., Li, R., Wang, S., Zhang, F., Wu, W., Xu, W.: ConSERT: A contrastive framework for self-supervised sentence representation transfer. In: Zong, C., Xia, F., Li, W., Navigli, R. (eds.) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 5065\u20135075. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.393","DOI":"10.18653\/v1\/2021.acl-long.393"},{"key":"738_CR15","volume-title":"Hyperbolic Graph Convolutional Neural Networks","author":"I Chami","year":"2019","unstructured":"Chami, I., Ying, R., Re, C., Leskovec, J.: Hyperbolic Graph Convolutional Neural Networks. Curran Associates Inc., Red Hook, NY, USA (2019)"},{"key":"738_CR16","doi-asserted-by":"publisher","unstructured":"Wan, Z., Cheng, F., Mao, Z., Liu, Q., Song, H., Li, J., Kurohashi, S.: GPT-RE: In-context learning for relation extraction using large language models. In: Bouamor, H., Pino, J., Bali, K. (eds.) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 3534\u20133547. Association for Computational Linguistics, Singapore (2023). https:\/\/doi.org\/10.18653\/v1\/2023.emnlp-main.214","DOI":"10.18653\/v1\/2023.emnlp-main.214"},{"key":"738_CR17","doi-asserted-by":"publisher","unstructured":"Xu, X., Zhu, Y., Wang, X., Zhang, N.: How to unleash the power of large language models for few-shot relation extraction? In: Sadat\u00a0Moosavi, N., Gurevych, I., Hou, Y., Kim, G., Kim, Y.J., Schuster, T., Agrawal, A. (eds.) Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), pp. 190\u2013200. Association for Computational Linguistics, Toronto, Canada (Hybrid) (2023). https:\/\/doi.org\/10.18653\/v1\/2023.sustainlp-1.13","DOI":"10.18653\/v1\/2023.sustainlp-1.13"},{"key":"738_CR18","doi-asserted-by":"publisher","DOI":"10.1145\/3649506","author":"J Yang","year":"2024","unstructured":"Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Zhong, S., Yin, B., Hu, X.: Harnessing the power of llms in practice: a survey on chatgpt and beyond. ACM Trans. Knowl. Discov. Data (2024). https:\/\/doi.org\/10.1145\/3649506","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"738_CR19","unstructured":"Longpre, S., Hou, L., Vu, T., Webson, A., Chung, H.W., Tay, Y., Zhou, D., Le, Q.V., Zoph, B., Wei, J., Roberts, A.: The flan collection: designing data and methods for effective instruction tuning. In: Proceedings of the 40th International Conference on Machine Learning. ICML\u201923. JMLR.org (2023)"},{"key":"738_CR20","unstructured":"Aone, C., Halverson, L., Hampton, T., Ramos-Santacruz, M.: SRA: Description of the IE2 system used for MUC-7. In: Seventh Message Understanding Conference (MUC-7): Proceedings of a Conference Held in Fairfax, Virginia, April 29 - May 1, 1998 (1998)"},{"key":"738_CR21","doi-asserted-by":"publisher","unstructured":"Zhou, P., Shi, W., Tian, J., Qi, Z., Li, B., Hao, H., Xu, B.: Attention-based bidirectional long short-term memory networks for relation classification. In: Erk, K., Smith, N.A. (eds.) Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 207\u2013212. Association for Computational Linguistics, Berlin, Germany (2016). https:\/\/doi.org\/10.18653\/v1\/P16-2034","DOI":"10.18653\/v1\/P16-2034"},{"key":"738_CR22","doi-asserted-by":"crossref","unstructured":"Zhou, W., Chen, M.: An improved baseline for sentence-level relation extraction. In: He, Y., Ji, H., Li, S., Liu, Y., Chang, C.-H. (eds.) Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 161\u2013168. Association for Computational Linguistics, Online only (2022)","DOI":"10.18653\/v1\/2022.aacl-short.21"},{"key":"738_CR23","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Qi, P., Manning, C.D.: Graph convolution over pruned dependency trees improves relation extraction. In: Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J. (eds.) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 2205\u20132215. Association for Computational Linguistics, Brussels, Belgium (2018). https:\/\/doi.org\/10.18653\/v1\/D18-1244","DOI":"10.18653\/v1\/D18-1244"},{"key":"738_CR24","doi-asserted-by":"publisher","unstructured":"Trisedya, B.D., Weikum, G., Qi, J., Zhang, R.: Neural relation extraction for knowledge base enrichment. In: Korhonen, A., Traum, D., M\u00e0rquez, L. (eds.) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 229\u2013240. Association for Computational Linguistics, Florence, Italy (2019). https:\/\/doi.org\/10.18653\/v1\/P19-1023","DOI":"10.18653\/v1\/P19-1023"},{"key":"738_CR25","volume-title":"Advances in Neural Information Processing Systems","author":"Z Yang","year":"2019","unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R.R., Le, Q.V.: Xlnet: generalized autoregressive pretraining for language understanding. In: Wallach, H., Larochelle, H., Beygelzimer, A., Alch\u00e9-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32. Curran Associates Inc., Newry (2019)"},{"key":"738_CR26","doi-asserted-by":"publisher","unstructured":"Xu, Y., Mou, L., Li, G., Chen, Y., Peng, H., Jin, Z.: Classifying relations via long short term memory networks along shortest dependency paths. In: M\u00e0rquez, L., Callison-Burch, C., Su, J. (eds.) Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1785\u20131794. Association for Computational Linguistics, Lisbon, Portugal (2015). https:\/\/doi.org\/10.18653\/v1\/D15-1206","DOI":"10.18653\/v1\/D15-1206"},{"key":"738_CR27","doi-asserted-by":"publisher","unstructured":"Tian, Y., Song, Y., Xia, F.: Improving relation extraction through syntax-induced pre-training with dependency masking. In: Muresan, S., Nakov, P., Villavicencio, A. (eds.) Findings of the Association for Computational Linguistics: ACL 2022, pp. 1875\u20131886. Association for Computational Linguistics, Dublin, Ireland (2022). https:\/\/doi.org\/10.18653\/v1\/2022.findings-acl.147","DOI":"10.18653\/v1\/2022.findings-acl.147"},{"key":"738_CR28","doi-asserted-by":"publisher","unstructured":"Xu, K., Reddy, S., Feng, Y., Huang, S., Zhao, D.: Question answering on Freebase via relation extraction and textual evidence. In: Erk, K., Smith, N.A. (eds.) Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 2326\u20132336. Association for Computational Linguistics, Berlin, Germany (2016). https:\/\/doi.org\/10.18653\/v1\/P16-1220","DOI":"10.18653\/v1\/P16-1220"},{"key":"738_CR29","doi-asserted-by":"publisher","unstructured":"Mandya, A., Bollegala, D., Coenen, F.: Graph convolution over multiple dependency sub-graphs for relation extraction. In: Scott, D., Bel, N., Zong, C. (eds.) Proceedings of the 28th International Conference on Computational Linguistics, pp. 6424\u20136435. International Committee on Computational Linguistics, Barcelona, Spain (Online) (2020). https:\/\/doi.org\/10.18653\/v1\/2020.coling-main.565","DOI":"10.18653\/v1\/2020.coling-main.565"},{"key":"738_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2023.102265","volume":"149","author":"T Wu","year":"2024","unstructured":"Wu, T., You, X., Xian, X., Pu, X., Qiao, S., Wang, C.: Towards deep understanding of graph convolutional networks for relation extraction. Data Knowl. Eng. 149, 102265 (2024)","journal-title":"Data Knowl. Eng."},{"key":"738_CR31","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.neucom.2021.10.091","volume":"471","author":"L Xiao","year":"2022","unstructured":"Xiao, L., Xue, Y., Wang, H., Hu, X., Gu, D., Zhu, Y.: Exploring fine-grained syntactic information for aspect-based sentiment classification with dual graph neural networks. Neurocomputing 471, 48\u201359 (2022). https:\/\/doi.org\/10.1016\/j.neucom.2021.10.091","journal-title":"Neurocomputing"},{"key":"738_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2024.103976","volume":"241","author":"S Yang","year":"2024","unstructured":"Yang, S., Xiao, L., Wu, X., Xu, J., Wang, L., He, L.: Simple contrastive learning in a self-supervised manner for robust visual question answering. Comput. Vis. Image Underst. 241, 103976 (2024). https:\/\/doi.org\/10.1016\/j.cviu.2024.103976","journal-title":"Comput. Vis. Image Underst."},{"key":"738_CR33","doi-asserted-by":"publisher","unstructured":"Xu, J., Yang, S., Xiao, L., Fu, Z., Wu, X., Ma, T., He, L.: Graph convolution over the semantic-syntactic hybrid graph enhanced by affective knowledge for aspect-level sentiment classification. In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138 (2022). https:\/\/doi.org\/10.1109\/IJCNN55064.2022.9892027","DOI":"10.1109\/IJCNN55064.2022.9892027"},{"key":"738_CR34","doi-asserted-by":"publisher","unstructured":"Wang, L., Cao, Z., Melo, G., Liu, Z.: Relation classification via multi-level attention CNNs. In: Erk, K., Smith, N.A. (eds.) Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1298\u20131307. Association for Computational Linguistics, Berlin, Germany (2016). https:\/\/doi.org\/10.18653\/v1\/P16-1123","DOI":"10.18653\/v1\/P16-1123"},{"key":"738_CR35","unstructured":"Zhuang, L., Wayne, L., Ya, S., Jun, Z.: A robustly optimized BERT pre-training approach with post-training. In: Li, S., Sun, M., Liu, Y., Wu, H., Liu, K., Che, W., He, S., Rao, G. (eds.) Proceedings of the 20th Chinese National Conference on Computational Linguistics, pp. 1218\u20131227. Chinese Information Processing Society of China, Huhhot, China (2021)"},{"issue":"4","key":"738_CR36","first-page":"215","volume":"10","author":"M Fr\u00e9chet","year":"1948","unstructured":"Fr\u00e9chet, M.: Les \u00e9l\u00e9ments al\u00e9atoires de nature quelconque dans un espace distanci\u00e9. Annales de l\u2019institut Henri Poincar\u00e9 10(4), 215\u2013310 (1948)","journal-title":"Annales de l\u2019institut Henri Poincar\u00e9"},{"key":"738_CR37","unstructured":"Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning, pp. 1597\u20131607 (2020). PMLR"},{"key":"738_CR38","doi-asserted-by":"crossref","unstructured":"Hendrickx, I., Kim, S.N., Kozareva, Z., Nakov, P., \u00d3\u00a0S\u00e9aghdha, D., Pad\u00f3, S., Pennacchiotti, M., Romano, L., Szpakowicz, S.: SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals. In: Erk, K., Strapparava, C. (eds.) Proceedings of the 5th International Workshop on Semantic Evaluation, pp. 33\u201338. Association for Computational Linguistics, Uppsala, Sweden (2010)","DOI":"10.3115\/1621969.1621986"},{"key":"738_CR39","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Zhong, V., Chen, D., Angeli, G., Manning, C.D.: Position-aware attention and supervised data improve slot filling. In: Palmer, M., Hwa, R., Riedel, S. (eds.) Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 35\u201345. Association for Computational Linguistics, Copenhagen, Denmark (2017). https:\/\/doi.org\/10.18653\/v1\/D17-1004","DOI":"10.18653\/v1\/D17-1004"},{"key":"738_CR40","doi-asserted-by":"publisher","unstructured":"Alt, C., Gabryszak, A., Hennig, L.: TACRED revisited: A thorough evaluation of the TACRED relation extraction task. In: Jurafsky, D., Chai, J., Schluter, N., Tetreault, J. (eds.) Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 1558\u20131569. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.142","DOI":"10.18653\/v1\/2020.acl-main.142"},{"key":"738_CR41","doi-asserted-by":"crossref","unstructured":"Stoica, G., Platanios, E.A., P\u2019oczos, B.: Re-tacred: Addressing shortcomings of the tacred dataset. In: AAAI Conference on Artificial Intelligence (2021)","DOI":"10.1609\/aaai.v35i15.17631"},{"issue":"1","key":"738_CR42","doi-asserted-by":"publisher","first-page":"8729621","DOI":"10.1155\/2024\/8729621","volume":"2024","author":"J Chen","year":"2024","unstructured":"Chen, J., Li, Z., Yu, H., Zhang, X.: A weighted diffusion graph convolutional network for relation extraction. J. Elect. Comput. Eng. 2024(1), 8729621 (2024)","journal-title":"J. Elect. Comput. Eng."},{"key":"738_CR43","doi-asserted-by":"publisher","unstructured":"Yang, R., Chen, Y., Yan, J., Qin, Y.: A graph with adaptive adjacency matrix for relation extraction. Computers, Materials & Continua 80(3), 4129\u20134147 (2024). https:\/\/doi.org\/10.32604\/cmc.2024.051675","DOI":"10.32604\/cmc.2024.051675"}],"container-title":["International Journal of Computational Intelligence Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44196-025-00738-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44196-025-00738-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44196-025-00738-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T09:51:03Z","timestamp":1738576263000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44196-025-00738-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,3]]},"references-count":43,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["738"],"URL":"https:\/\/doi.org\/10.1007\/s44196-025-00738-2","relation":{},"ISSN":["1875-6883"],"issn-type":[{"value":"1875-6883","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,3]]},"assertion":[{"value":"3 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 February 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This research did not involve human participants, animals, or sensitive data, and therefore, ethics approval and consent to participate were not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval and Consent to Participate"}},{"value":"Consent for publication was not applicable to this study as it did not involve identifiable human data or images.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}}],"article-number":"18"}}