{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T12:48:35Z","timestamp":1770814115556,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T00:00:00Z","timestamp":1764806400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T00:00:00Z","timestamp":1764806400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s00530-025-02055-2","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T07:02:19Z","timestamp":1764831739000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dual-consistency framework for cross-domain zero-shot image retrieval via prompt reconstruction and semantic mining"],"prefix":"10.1007","volume":"32","author":[{"given":"Haoxiang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deqiang","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiqi","family":"Kou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"key":"2055_CR1","doi-asserted-by":"crossref","unstructured":"Wang, S., Yu, L., Li, C., Fu, C.-W., Heng, P.-A.: Learning from extrinsic and intrinsic supervisions for domain generalization. In: European Conference on Computer Vision, pp. 159\u2013176 (2020). Springer","DOI":"10.1007\/978-3-030-58545-7_10"},{"issue":"6","key":"2055_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00530-024-01539-x","volume":"30","author":"H Kang","year":"2024","unstructured":"Kang, H., Zhang, X., Han, W., Zhou, M.: Dark knowledge association guided hashing for unsupervised cross-modal retrieval. Multimedia Systems 30(6), 1\u201313 (2024)","journal-title":"Multimedia Systems"},{"issue":"2","key":"2055_CR3","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1007\/s00530-025-01749-x","volume":"31","author":"L Liu","year":"2025","unstructured":"Liu, L., Kong, M., Cao, C., Shu, Z., Liu, K., Li, X., Hou, M.: Personalized music recommendation algorithm based on machine learning. Multimedia Syst. 31(2), 166 (2025)","journal-title":"Multimedia Syst."},{"issue":"5","key":"2055_CR4","doi-asserted-by":"publisher","first-page":"1224","DOI":"10.1109\/TPAMI.2017.2709749","volume":"40","author":"L Zheng","year":"2017","unstructured":"Zheng, L., Yang, Y., Tian, Q.: SIFT meets CNN: A decade survey of instance retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 40(5), 1224\u20131244 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"10","key":"2055_CR5","doi-asserted-by":"publisher","first-page":"7177","DOI":"10.1109\/TCSVT.2022.3171972","volume":"32","author":"H Sun","year":"2022","unstructured":"Sun, H., Xu, J., Wang, J., Qi, Q., Ge, C., Liao, J.: Dli-net: dual local interaction network for fine-grained sketch-based image retrieval. IEEE Transactions on Circuits and Systems for Video Technology 32(10), 7177\u20137189 (2022)","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"2055_CR6","doi-asserted-by":"crossref","unstructured":"Cao, Y., Wang, C., Zhang, L., Zhang, L.: Edgel index for large-scale sketch-based image search. In: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, pp. 761\u2013768 (2011)","DOI":"10.1109\/CVPR.2011.5995460"},{"key":"2055_CR7","doi-asserted-by":"crossref","unstructured":"Paul, S., Dutta, T., Biswas, S.: Universal cross-domain retrieval: Generalizing across classes and domains. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12056\u201312064 (2021)","DOI":"10.1109\/ICCV48922.2021.01184"},{"key":"2055_CR8","doi-asserted-by":"crossref","unstructured":"Agarwal, A., Karanam, S., Srinivasan, B.V., Banerjee, B.: Contrastive learning of semantic concepts for open-set cross-domain retrieval. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 4115\u20134124 (2023)","DOI":"10.1109\/WACV56688.2023.00410"},{"key":"2055_CR9","unstructured":"Chen, F., Zhang, D., Han, M., Chen, X., Shi, J., Xu, S., Xu, B.: Vlp: A survey on vision-language pre-training. arXiv preprint arXiv:2202.09061 (2022)"},{"key":"2055_CR10","doi-asserted-by":"crossref","unstructured":"Du, Y., Liu, Z., Li, J., Zhao, W.X.: A survey of vision-language pre-trained models. arXiv preprint arXiv:2202.10936 (2022)","DOI":"10.24963\/ijcai.2022\/762"},{"key":"2055_CR11","unstructured":"Li, Y., Liang, F., Zhao, L., Cui, Y., Ouyang, W., Shao, J., Yu, F., Yan, J.: Supervision exists everywhere: A data efficient contrastive language-image pre-training paradigm. arXiv preprint arXiv:2110.05208 (2021)"},{"key":"2055_CR12","unstructured":"Luo, Y., Yang, Z., Meng, F., Li, Y., Zhou, J., Zhang, Y.: An empirical study of catastrophic forgetting in large language models during continual fine-tuning. arXiv preprint arXiv:2308.08747 (2023)"},{"key":"2055_CR13","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.: Language models are few-shot learners. Adv. Neural. Inf. Process. Syst. 33, 1877\u20131901 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"2055_CR14","doi-asserted-by":"crossref","unstructured":"Jia, M., Tang, L., Chen, B.-C., Cardie, C., Belongie, S., Hariharan, B., Lim, S.-N.: Visual prompt tuning. In: European Conference on Computer Vision, pp. 709\u2013727 (2022). Springer","DOI":"10.1007\/978-3-031-19827-4_41"},{"key":"2055_CR15","doi-asserted-by":"crossref","unstructured":"Qian, Z., Wang, X., Duan, X., Qin, P., Li, Y., Zhu, W.: Decouple before interact: Multi-modal prompt learning for continual visual question answering. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2953\u20132962 (2023)","DOI":"10.1109\/ICCV51070.2023.00276"},{"key":"2055_CR16","doi-asserted-by":"crossref","unstructured":"Zhu, J., Lai, S., Chen, X., Wang, D., Lu, H.: Visual prompt multi-modal tracking. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9516\u20139526 (2023)","DOI":"10.1109\/CVPR52729.2023.00918"},{"issue":"9","key":"2055_CR17","doi-asserted-by":"publisher","first-page":"2337","DOI":"10.1007\/s11263-022-01653-1","volume":"130","author":"K Zhou","year":"2022","unstructured":"Zhou, K., Yang, J., Loy, C.C., Liu, Z.: Learning to prompt for vision-language models. International Journal of Computer Vision 130(9), 2337\u20132348 (2022)","journal-title":"International Journal of Computer Vision"},{"key":"2055_CR18","unstructured":"Dhillon, G.S., Chaudhari, P., Ravichandran, A., Soatto, S.: A baseline for few-shot image classification. arXiv preprint arXiv:1909.02729 (2019)"},{"key":"2055_CR19","doi-asserted-by":"crossref","unstructured":"Yao, H., Zhang, R., Xu, C.: Tcp: textual-based class-aware prompt tuning for visual-language model. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 23438\u201323448 (2024)","DOI":"10.1109\/CVPR52733.2024.02212"},{"key":"2055_CR20","unstructured":"Hassan, J., Gani, H., Hussein, N., Khattak, M.U., Naseer, M., Khan, F.S., Khan, S.: Align your prompts: Test-time prompting with distribution alignment for zero-shot generalization. arXiv preprint arXiv:2311.01459 (2023)"},{"key":"2055_CR21","doi-asserted-by":"crossref","unstructured":"Rasheed, H., Khattak, M.U., Maaz, M., Khan, S., Khan, F.S.: Fine-tuned clip models are efficient video learners. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6545\u20136554 (2023)","DOI":"10.1109\/CVPR52729.2023.00633"},{"key":"2055_CR22","doi-asserted-by":"crossref","unstructured":"Khattak, M.U., Rasheed, H., Maaz, M., Khan, S., Khan, F.S.: Maple: Multi-modal prompt learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 19113\u201319122 (2023)","DOI":"10.1109\/CVPR52729.2023.01832"},{"key":"2055_CR23","unstructured":"Roy, S., Etemad, A.: Consistency-guided prompt learning for vision-language models. In: The Twelfth International Conference on Learning Representations (ICLR) (2024)"},{"key":"2055_CR24","doi-asserted-by":"crossref","unstructured":"Mistretta, M., Baldrati, A., Bertini, M., Bagdanov, A.D.: Improving zero-shot generalization of learned prompts via unsupervised knowledge distillation. In: European Conference on Computer Vision, pp. 459\u2013477 (2024). Springer","DOI":"10.1007\/978-3-031-72907-2_27"},{"issue":"7600","key":"2055_CR25","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1038\/nature17637","volume":"532","author":"AG Huth","year":"2016","unstructured":"Huth, A.G., De Heer, W.A., Griffiths, T.L., Theunissen, F.E., Gallant, J.L.: Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532(7600), 453\u2013458 (2016)","journal-title":"Nature"},{"issue":"3\u20134","key":"2055_CR26","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1080\/02643294.2016.1147426","volume":"33","author":"JR Binder","year":"2016","unstructured":"Binder, J.R., Conant, L.L., Humphries, C.J., Fernandino, L., Simons, S.B., Aguilar, M., Desai, R.H.: Toward a brain-based componential semantic representation. Cogn. Neuropsychol. 33(3\u20134), 130\u2013174 (2016)","journal-title":"Cogn. Neuropsychol."},{"key":"2055_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, K., Zhang, L., Hu, B., Zhu, M., Mao, Z.: Unlocking the power of cross-dimensional semantic dependency for image-text matching. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 4828\u20134837 (2023)","DOI":"10.1145\/3581783.3611703"},{"key":"2055_CR28","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1016\/S0079-6123(01)34028-1","volume":"134","author":"A Pascual-Leone","year":"2001","unstructured":"Pascual-Leone, A., Hamilton, R.: The metamodal organization of the brain. Prog. Brain Res. 134, 427\u2013445 (2001)","journal-title":"Prog. Brain Res."},{"issue":"11","key":"2055_CR29","doi-asserted-by":"publisher","first-page":"2332","DOI":"10.1109\/TPAMI.2015.2408354","volume":"37","author":"Y Fu","year":"2015","unstructured":"Fu, Y., Hospedales, T.M., Xiang, T., Gong, S.: Transductive multi-view zero-shot learning. IEEE Trans. Pattern Anal. Mach. Intell. 37(11), 2332\u20132345 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"2055_CR30","first-page":"4396","volume":"45","author":"K Zhou","year":"2022","unstructured":"Zhou, K., Liu, Z., Qiao, Y., Xiang, T., Loy, C.C.: Domain generalization: A survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(4), 4396\u20134415 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2055_CR31","doi-asserted-by":"crossref","unstructured":"Liu, Q., Xie, L., Wang, H., Yuille, A.L.: Semantic-aware knowledge preservation for zero-shot sketch-based image retrieval. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3662\u20133671 (2019)","DOI":"10.1109\/ICCV.2019.00376"},{"key":"2055_CR32","doi-asserted-by":"publisher","first-page":"12943","DOI":"10.1609\/aaai.v34i07.6993","volume":"34","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Zhang, Y., Feng, R., Zhang, T., Fan, W.: Zero-shot sketch-based image retrieval via graph convolution network. Proceedings of the AAAI Conference on Artificial Intelligence 34, 12943\u201312950 (2020)","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"2055_CR33","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1109\/LSP.2020.3043972","volume":"28","author":"Z Yang","year":"2021","unstructured":"Yang, Z., Zhu, X., Qian, J., Liu, P.: Dark-aware network for fine-grained sketch-based image retrieval. IEEE Signal Process. Lett. 28, 264\u2013268 (2021). https:\/\/doi.org\/10.1109\/LSP.2020.3043972","journal-title":"IEEE Signal Process. Lett."},{"key":"2055_CR34","doi-asserted-by":"publisher","first-page":"2833","DOI":"10.1109\/TMM.2020.3017918","volume":"23","author":"T Dutta","year":"2020","unstructured":"Dutta, T., Singh, A., Biswas, S.: Styleguide: zero-shot sketch-based image retrieval using style-guided image generation. IEEE Trans. Multimedia 23, 2833\u20132842 (2020)","journal-title":"IEEE Trans. Multimedia"},{"key":"2055_CR35","doi-asserted-by":"publisher","unstructured":"Dey, S., Riba, P., Dutta, A., Llad\u00f3s, J.L., Song, Y.-Z.: Doodle to search: Practical zero-shot sketch-based image retrieval. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2174\u20132183 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00228","DOI":"10.1109\/CVPR.2019.00228"},{"key":"2055_CR36","doi-asserted-by":"crossref","unstructured":"Dutta, A., Akata, Z.: Semantically tied paired cycle consistency for zero-shot sketch-based image retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5089\u20135098 (2019)","DOI":"10.1109\/CVPR.2019.00523"},{"key":"2055_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2024.102398","volume":"60","author":"H Zhang","year":"2024","unstructured":"Zhang, H., Cheng, D., Kou, Q., Asad, M., Jiang, H.: Indicative vision transformer for end-to-end zero-shot sketch-based image retrieval. Advanced Engineering Informatics 60, 102398 (2024)","journal-title":"Advanced Engineering Informatics"},{"key":"2055_CR38","unstructured":"Roth, K., Milbich, T., Sinha, S., Gupta, P., Ommer, B., Cohen, J.P.: Revisiting training strategies and generalization performance in deep metric learning. In: International Conference on Machine Learning, pp. 8242\u20138252 (2020). PMLR"},{"key":"2055_CR39","doi-asserted-by":"crossref","unstructured":"Lin, J., Yin, H., Ping, W., Molchanov, P., Shoeybi, M., Han, S.: Vila: On pre-training for visual language models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 26689\u201326699 (2024)","DOI":"10.1109\/CVPR52733.2024.02520"},{"key":"2055_CR40","doi-asserted-by":"crossref","unstructured":"Ding, N., Hu, S., Zhao, W., Chen, Y., Liu, Z., Zheng, H.-T., Sun, M.: Openprompt: An open-source framework for prompt-learning. arXiv preprint arXiv:2111.01998 (2021)","DOI":"10.18653\/v1\/2022.acl-demo.10"},{"key":"2055_CR41","doi-asserted-by":"crossref","unstructured":"Sariyildiz, M.B., Kalantidis, Y., Larlus, D., Alahari, K.: Concept generalization in visual representation learning. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9629\u20139639 (2021)","DOI":"10.1109\/ICCV48922.2021.00949"},{"key":"2055_CR42","unstructured":"Wang, Z., Liang, J., He, R., Xu, N., Wang, Z., Tan, T.: Improving zero-shot generalization for clip with synthesized prompts. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 3032\u20133042 (2023)"},{"key":"2055_CR43","unstructured":"Kingma, D.P., Welling, M., et al.: Auto-encoding variational bayes. Banff, Canada (2013)"},{"issue":"4","key":"2055_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2897824.2925954","volume":"35","author":"P Sangkloy","year":"2016","unstructured":"Sangkloy, P., Burnell, N., Ham, C., Hays, J.: The sketchy database: learning to retrieve badly drawn bunnies. ACM Trans. Graph. 35(4), 1\u201312 (2016)","journal-title":"ACM Trans. Graph."},{"issue":"5","key":"2055_CR45","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.cag.2010.07.002","volume":"34","author":"M Eitz","year":"2010","unstructured":"Eitz, M., Hildebrand, K., Boubekeur, T., Alexa, M.: An evaluation of descriptors for large-scale image retrieval from sketched feature lines. Computers & Graphics 34(5), 482\u2013498 (2010)","journal-title":"Computers & Graphics"},{"key":"2055_CR46","doi-asserted-by":"crossref","unstructured":"Venkateswara, H., Eusebio, J., Chakraborty, S., Panchanathan, S.: Deep hashing network for unsupervised domain adaptation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5018\u20135027 (2017)","DOI":"10.1109\/CVPR.2017.572"},{"key":"2055_CR47","doi-asserted-by":"crossref","unstructured":"Peng, X., Bai, Q., Xia, X., Huang, Z., Saenko, K., Wang, B.: Moment Matching for Multi-Source Domain Adaptation (2019). https:\/\/arxiv.org\/abs\/1812.01754","DOI":"10.1109\/ICCV.2019.00149"},{"issue":"12","key":"2055_CR48","doi-asserted-by":"publisher","first-page":"9181","DOI":"10.1109\/TPAMI.2021.3123315","volume":"44","author":"H Wang","year":"2021","unstructured":"Wang, H., Deng, C., Liu, T., Tao, D.: Transferable coupled network for zero-shot sketch-based image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 44(12), 9181\u20139194 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2055_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108528","volume":"126","author":"O Tursun","year":"2022","unstructured":"Tursun, O., Denman, S., Sridharan, S., Goan, E., Fookes, C.: An efficient framework for zero-shot sketch-based image retrieval. Pattern Recognit. 126, 108528 (2022). https:\/\/doi.org\/10.1016\/j.patcog.2022.108528","journal-title":"Pattern Recognit."},{"issue":"2","key":"2055_CR50","doi-asserted-by":"publisher","first-page":"2370","DOI":"10.1609\/aaai.v36i2.20136","volume":"36","author":"J Tian","year":"2022","unstructured":"Tian, J., Xu, X., Shen, F., Yang, Y., Shen, H.T.: TVT: Three-Way Vision Transformer through Multi-Modal Hypersphere Learning for Zero-Shot Sketch-Based Image Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence 36(2), 2370\u20132378 (2022). https:\/\/doi.org\/10.1609\/aaai.v36i2.20136","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"2055_CR51","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i6.32662","author":"BH Ngo","year":"2025","unstructured":"Ngo, B.H., Bui, D.C., Do-Tran, N.-T., Choi, T.J.: Higda: hierarchical graph of nodes to learn local-to-global topology for semi-supervised domain adaptation. Proceedings of the AAAI Conference on Artificial Intelligence (2025). https:\/\/doi.org\/10.1609\/aaai.v39i6.32662","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"2055_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.126597","volume":"271","author":"BH Ngo","year":"2025","unstructured":"Ngo, B.H., Bui, D.C., Choi, T.J.: How to enrich cross-domain representations? data augmentation, cycle-pseudo labeling, and category-aware graph learning. Expert Systems with Applications 271, 126597 (2025)","journal-title":"Expert Systems with Applications"},{"key":"2055_CR53","doi-asserted-by":"crossref","unstructured":"Ngo, B.H., Jeong\u00a0Chae, Y., Kwon, J.E., Hyeon\u00a0Park, J., Cho, S.I.: Improved knowledge transfer for semi-supervised domain adaptation via trico training strategy. In: 2023 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 19157\u201319166","DOI":"10.1109\/ICCV51070.2023.01760"},{"key":"2055_CR54","doi-asserted-by":"publisher","first-page":"134969","DOI":"10.1109\/ACCESS.2023.3337438","volume":"11","author":"BH Ngo","year":"2023","unstructured":"Ngo, B.H., Chae, Y.J., Park, S.J., Kim, J.H., Cho, S.I.: Multiple tasks-based multi-source domain adaptation using divide-and-conquer strategy. IEEE Access 11, 134969\u2013134985 (2023)","journal-title":"IEEE Access"},{"key":"2055_CR55","unstructured":"Kim, J., Ngo, B., Park, J., Kwon, J., Lee, H., Cho, S.: Distilling and Refining Domain-Specific Knowledge for Semi-Supervised Domain Adaptation. (2022). 33rd British Machine Vision Conference Proceedings, BMVC 2022"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-025-02055-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-025-02055-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-025-02055-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T04:19:02Z","timestamp":1770783542000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-025-02055-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,4]]},"references-count":55,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["2055"],"URL":"https:\/\/doi.org\/10.1007\/s00530-025-02055-2","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,4]]},"assertion":[{"value":"13 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 December 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 conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"9"}}