{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T23:52:40Z","timestamp":1785887560951,"version":"3.56.0"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T00:00:00Z","timestamp":1779753600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:00:00Z","timestamp":1785888000000},"content-version":"vor","delay-in-days":71,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-54981-4","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T15:43:28Z","timestamp":1779810208000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-agent collaboration for coherent long-video music synthesis"],"prefix":"10.1038","volume":"16","author":[{"given":"Yipin","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,26]]},"reference":[{"issue":"2","key":"54981_CR1","first-page":"201","volume":"1","author":"JH Kam","year":"2024","unstructured":"Kam, J. H. et al. Exploring current and future technologies to make sense of the biophoton phenomenon: a narrative review. Adv. Technol. Neurosci. 1(2), 201\u2013210 (2024).","journal-title":"Adv. Technol. Neurosci."},{"key":"54981_CR2","unstructured":"Jiayi, F., Zheyun, Q., Xiaoming, X., Xiushan, N. & Yilong, Y. Spot: Spatiotemporal prompt optimization for motion-stabilized mllm-guided video segmentation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2026)."},{"issue":"2","key":"54981_CR3","first-page":"188","volume":"1","author":"M Zhang","year":"2024","unstructured":"Zhang, M. et al. The application of integrating electroencephalograph-based emotion recognition technology into brain-computer interface systems for the treatment of depression: a narrative review. Adv. Technol. Neurosci. 1(2), 188\u2013200 (2024).","journal-title":"Adv. Technol. Neurosci."},{"issue":"4","key":"54981_CR4","first-page":"145","volume":"2","author":"AR Zhao","year":"2025","unstructured":"Zhao, A. R., Yuan, R., Kouznetsova, V. L. & Tsigelny, I. F. Application of machine learning technology and mirna biomarkers: A novel approach for epilepsy diagnosis. Adv. Technol. Neurosci. 2(4), 145\u2013151 (2025).","journal-title":"Adv. Technol. Neurosci."},{"key":"54981_CR5","doi-asserted-by":"crossref","unstructured":"Qin, Z., Lu, X., Nie, X., Yin, Y. & Shen, J. Exposing the self-supervised space-time correspondence learning via graph kernels. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 37, 2110\u20132118 (2023).","DOI":"10.1609\/aaai.v37i2.25304"},{"issue":"6","key":"54981_CR6","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1016\/j.vrih.2023.06.003","volume":"5","author":"M Wang","year":"2023","unstructured":"Wang, M., Meng, M., Liu, J. & Wu, J. Adequate alignment and interaction for cross-modal retrieval. Virtual Reality Intell. Hardware 5(6), 509\u2013522 (2023).","journal-title":"Virtual Reality Intell. Hardware"},{"key":"54981_CR7","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","volume":"25","author":"N Jiang","year":"2022","unstructured":"Jiang, N., Sheng, B., Li, P. & Lee, T.-Y. Photohelper: portrait photographing guidance via deep feature retrieval and fusion. IEEE Trans. Multimedia 25, 2226\u20132238 (2022).","journal-title":"IEEE Trans. Multimedia"},{"key":"54981_CR8","doi-asserted-by":"crossref","unstructured":"Fan, Y., Ma, X., Wu, R., Du, Y., Li, J., Gao, Z. & Li, Q. Videoagent: A memory-augmented multimodal agent for video understanding. In European Conference on Computer Vision, pp. 75\u201392 (2024) Springer.","DOI":"10.1007\/978-3-031-72670-5_5"},{"key":"54981_CR9","doi-asserted-by":"crossref","unstructured":"He, B., Li, H., Jang, Y.K., Jia, M., Cao, X., Shah, A., Shrivastava, A. & Lim, S.-N. Ma-lmm: Memory-augmented large multimodal model for long-term video understanding. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13504\u201313514 (2024).","DOI":"10.1109\/CVPR52733.2024.01282"},{"key":"54981_CR10","doi-asserted-by":"publisher","first-page":"6821","DOI":"10.1109\/TMM.2022.3214776","volume":"25","author":"J Zhu","year":"2022","unstructured":"Zhu, J. et al. Fffn: Frame-by-frame feedback fusion network for video super-resolution. IEEE Trans. Multimedia 25, 6821\u20136835 (2022).","journal-title":"IEEE Trans. Multimedia"},{"key":"54981_CR11","doi-asserted-by":"crossref","unstructured":"Rong, Y., Wang, J., Lei, G., Yang, S. & Liu, L. Audiogenie: A training-free multi-agent framework for diverse multimodality-to-multiaudio generation. In Proceedings of the 33rd ACM International Conference on Multimedia 8872\u20138881 (2025).","DOI":"10.1145\/3746027.3755758"},{"key":"54981_CR12","doi-asserted-by":"crossref","unstructured":"Iashin, V. & Rahtu, E. Taming visually guided sound generation. arXiv preprint arXiv:2110.08791 (2021).","DOI":"10.5244\/C.35.336"},{"issue":"1","key":"54981_CR13","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1007\/s11263-025-02649-3","volume":"134","author":"Y Zhang","year":"2026","unstructured":"Zhang, Y. et al. Foleycrafter: Bring silent videos to life with lifelike and synchronized sounds. Int. J. Comput. Vision 134(1), 46 (2026).","journal-title":"Int. J. Comput. Vision"},{"key":"54981_CR14","doi-asserted-by":"crossref","unstructured":"Cheng, H. K. et al. Mmaudio: Taming multimodal joint training for high-quality video-to-audio synthesis. In Proceedings of the Computer Vision and Pattern Recognition Conference 28901\u201328911 (2025).","DOI":"10.1109\/CVPR52734.2025.02691"},{"issue":"3","key":"54981_CR15","doi-asserted-by":"publisher","first-page":"70044","DOI":"10.1002\/cav.70044","volume":"36","author":"J Jiao","year":"2025","unstructured":"Jiao, J., Zeng, R., Dai, J. & Pan, J. Bach: Bi-stage data-driven piano performance animation for controllable hand motion. Comput. Anim. Virtual Worlds 36(3), 70044 (2025).","journal-title":"Comput. Anim. Virtual Worlds"},{"issue":"5","key":"54981_CR16","doi-asserted-by":"publisher","first-page":"3345","DOI":"10.1007\/s00371-024-03606-w","volume":"41","author":"W-H Kai","year":"2025","unstructured":"Kai, W.-H. & Xing, K.-X. Video-driven musical composition using large language model with memory-augmented state space. Vis. Comput. 41(5), 3345\u20133357 (2025).","journal-title":"Vis. Comput."},{"key":"54981_CR17","doi-asserted-by":"crossref","unstructured":"Hong, S., Im, W. & Yang, H. S. Cbvmr: content-based video-music retrieval using soft intra-modal structure constraint. In Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval 353\u2013361 (2018).","DOI":"10.1145\/3206025.3206046"},{"key":"54981_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123640","volume":"249","author":"J Kang","year":"2024","unstructured":"Kang, J., Poria, S. & Herremans, D. Video2music: Suitable music generation from videos using an affective multimodal transformer model. Expert Syst. Appl. 249, 123640 (2024).","journal-title":"Expert Syst. Appl."},{"key":"54981_CR19","doi-asserted-by":"crossref","unstructured":"Tian, Z., Liu, Z., Yuan, R., Pan, J., Liu, Q., Tan, X., Chen, Q., Xue, W. & Guo, Y. Vidmuse: A simple video-to-music generation framework with long-short-term modeling. In Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 18782\u201318793 (2025).","DOI":"10.1109\/CVPR52734.2025.01750"},{"key":"54981_CR20","doi-asserted-by":"publisher","first-page":"6543","DOI":"10.1109\/TIP.2023.3328485","volume":"32","author":"Z Qin","year":"2023","unstructured":"Qin, Z. et al. Reformulating graph kernels for self-supervised space-time correspondence learning. IEEE Trans. Image Process. 32, 6543\u20136557 (2023).","journal-title":"IEEE Trans. Image Process."},{"key":"54981_CR21","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Xu, X., Xu, X., Zhang, D., Liu, L. & Chen, Y.-C. Orchestrating audio: Multi-agent framework for long-video audio synthesis. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pp. 22278\u201322293 (2025).","DOI":"10.18653\/v1\/2025.emnlp-main.1133"},{"key":"54981_CR22","doi-asserted-by":"crossref","unstructured":"Lei, W. et al. A comprehensive survey on multi-agent systems for audio-visual generation and understanding Authorea Preprints (2025).","DOI":"10.36227\/techrxiv.176583352.26143196\/v1"},{"issue":"2","key":"54981_CR23","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1007\/s11263-025-02650-w","volume":"134","author":"H Li","year":"2026","unstructured":"Li, H., Li, L., Wang, H., Zhang, W. & Ren, P. Large foundation model empowered region-aware underwater image captioning. Int. J. Comput. Vis. 134(2), 66 (2026).","journal-title":"Int. J. Comput. Vis."},{"key":"54981_CR24","doi-asserted-by":"crossref","unstructured":"Li, H., Li, L., Wang, H., Zhang, W. & Ren, P. Underwater image captioning with aquasketch-enhanced cross-scale information fusion. IEEE Trans. Geosci. Remote Sens. (2025).","DOI":"10.1109\/TGRS.2025.3585119"},{"issue":"1","key":"54981_CR25","first-page":"1","volume":"42","author":"D Wang","year":"2023","unstructured":"Wang, D. et al. Multi-view enhanced graph attention network for session-based music recommendation. ACM Trans. Inf. Syst. 42(1), 1\u201330 (2023).","journal-title":"ACM Trans. Inf. Syst."},{"key":"54981_CR26","doi-asserted-by":"crossref","unstructured":"Yang, Q., Wang, S., Guo, D., Yu, D., Xiao, Q., Wang, D. & Luo, C. Cascading multimodal feature enhanced contrast learning for music recommendation. In 2024 IEEE International Conference on Data Mining (ICDM), pp. 905\u2013910 (2024) IEEE.","DOI":"10.1109\/ICDM59182.2024.00113"},{"key":"54981_CR27","doi-asserted-by":"crossref","unstructured":"Wang, S., Ouyang, T., Xiao, Q., Wang, D., Ren, Y., Xu, S., Guo, D. & Luo, C. Progressive semantic residual quantization for multimodal-joint interest modeling in music recommendation. In Proceedings of the 34th ACM International Conference on Information and Knowledge Management, pp. 6119\u20136127 (2025).","DOI":"10.1145\/3746252.3761579"},{"key":"54981_CR28","doi-asserted-by":"crossref","unstructured":"Wang, J., Duan, H., Zhao, Y., Wang, J., Zhai, G. & Min, X. Lmm4lmm: Benchmarking and evaluating large-multimodal image generation with lmms. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 17312\u201317323 (2025).","DOI":"10.1109\/ICCV51701.2025.01608"},{"key":"54981_CR29","doi-asserted-by":"crossref","unstructured":"Wang, J., Duan, H., Zhai, G., Wang, J. & Min, X. Aigv-assessor: Benchmarking and evaluating the perceptual quality of text-to-video generation with lmm. In Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 18869\u201318880 (2025).","DOI":"10.1109\/CVPR52734.2025.01758"},{"key":"54981_CR30","doi-asserted-by":"crossref","unstructured":"Wang, J., Duan, H., Zhai, G. & Min, X. Quality assessment for ai generated images with instruction tuning. IEEE Trans. Multimedia (2026).","DOI":"10.1109\/TMM.2026.3651009"},{"key":"54981_CR31","unstructured":"Wang, J., Duan, H., Jia, Z., Zhao, Y., Yang, W.Y., Zhang, Z., Chen, Z., Wang, J., Xing, Y., Zhai, G., et al. Love: Benchmarking and evaluating text-to-video generation and video-to-text interpretation. arXiv preprint arXiv:2505.12098 (2025)."},{"key":"54981_CR32","doi-asserted-by":"crossref","unstructured":"Min, X. et al. Exploring rich subjective quality information for image quality assessment in the wild. In IEEE Transactions on Circuits and Systems for Video Technology (2025).","DOI":"10.1109\/TCSVT.2025.3544659"},{"key":"54981_CR33","unstructured":"Wang, J., Wang, J., Duan, H., Kang, J., Zhai, G. & Min, X. I2i-bench: A comprehensive benchmark suite for image-to-image editing models. arXiv preprint arXiv:2512.04660 (2025)."},{"key":"54981_CR34","unstructured":"Yan, W., Zhang, Y., Abbeel, P. & Srinivas, A. Videogpt: Video generation using vq-vae and transformers (2021) arXiv:2104.10157 arXiv preprint."},{"key":"54981_CR35","unstructured":"Liu, Y., Zhang, K., Li, Y., Yan, Z., Gao, C., Chen, R., Yuan, Z., Huang, Y., Sun, H., Gao, J. et al. Sora: A review on background, technology, limitations, and opportunities of large vision models. arXiv preprint arXiv:2402.17177 (2024)."},{"issue":"3","key":"54981_CR36","doi-asserted-by":"publisher","first-page":"70058","DOI":"10.1002\/cav.70058","volume":"36","author":"W Zhou","year":"2025","unstructured":"Zhou, W., Shen, W. & Meng, X. An improved social force model-driven multi-agent generative adversarial imitation learning framework for pedestrian trajectory prediction. Comput. Anim. Virtual Worlds 36(3), 70058 (2025).","journal-title":"Comput. Anim. Virtual Worlds"},{"key":"54981_CR37","unstructured":"Hong, S., Zhuge, M., Chen, J., Zheng, X., Cheng, Y., Wang, J., Zhang, C., Wang, Z., Yau, S.K.S., Lin, Z. et al Metagpt: Meta programming for a multi-agent collaborative framework. In The Twelfth International Conference on Learning Representations (2023)."},{"key":"54981_CR38","doi-asserted-by":"crossref","unstructured":"Qian, C., Liu, W., Liu, H., Chen, N., Dang, Y., Li, J., Yang, C., Chen, W., Su, Y., Cong, X. et al. Chatdev: Communicative agents for software development. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (volume 1: Long Papers), pp. 15174\u201315186 (2024).","DOI":"10.18653\/v1\/2024.acl-long.810"},{"key":"54981_CR39","doi-asserted-by":"crossref","unstructured":"Huang, R., Li, M., Yang, D., Shi, J., Chang, X., Ye, Z., Wu, Y., Hong, Z., Huang, J., Liu, J. et al. Audiogpt: Understanding and generating speech, music, sound, and talking head. In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, pp. 23802\u201323804 (2024).","DOI":"10.1609\/aaai.v38i21.30570"},{"key":"54981_CR40","unstructured":"Zhang, Y., Xu, X., Xu, X., Liu, L., Chen, Y. Long-video audio synthesis with multi-agent collaboration. arXiv preprint arXiv:2503.10719 (2025)."},{"issue":"4","key":"54981_CR41","first-page":"152","volume":"2","author":"X Chen","year":"2025","unstructured":"Chen, X., Zhuang, J. & Gao, Z. Synchronization for chaotic neural networks based on sampled data: A novel neuroscience technology using time-squared augmented lyapunov functional. Adv. Technol. Neurosci. 2(4), 152\u2013160 (2025).","journal-title":"Adv. Technol. Neurosci."},{"key":"54981_CR42","doi-asserted-by":"crossref","unstructured":"Wen, Y. et al. Sat-net: structure-aware transformer-based attention fusion network for low-quality retinal fundus images enhancement. IEEE Trans. Multimedia (2025).","DOI":"10.1109\/TMM.2025.3565935"},{"issue":"3","key":"54981_CR43","doi-asserted-by":"publisher","first-page":"2011","DOI":"10.1007\/s00371-024-03520-1","volume":"41","author":"S Liu","year":"2025","unstructured":"Liu, S. et al. Cmt-6d: a lightweight iterative 6dof pose estimation network based on cross-modal transformer. Vis. Comput. 41(3), 2011\u20132027 (2025).","journal-title":"Vis. Comput."},{"key":"54981_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112258","volume":"301","author":"Y Ma","year":"2024","unstructured":"Ma, Y. et al. Style-aware two-stage learning framework for video captioning. Knowl.-Based Syst. 301, 112258 (2024).","journal-title":"Knowl.-Based Syst."},{"key":"54981_CR45","doi-asserted-by":"crossref","unstructured":"Ma, Y. et al. Retta: Retrieval-enhanced test-time adaptation for zero-shot video captioning. Pattern Recogn. 112170 (2025).","DOI":"10.1016\/j.patcog.2025.112170"},{"key":"54981_CR46","doi-asserted-by":"publisher","first-page":"10078","DOI":"10.52202\/068431-0732","volume":"35","author":"Z Tong","year":"2022","unstructured":"Tong, Z., Song, Y., Wang, J. & Wang, L. Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training. Adv. Neural. Inf. Process. Syst. 35, 10078\u201310093 (2022).","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"54981_CR47","doi-asserted-by":"crossref","unstructured":"Arnab, A. et al. Vivit: A video vision transformer. In Proceedings of the IEEE\/CVF International Conference on Computer Vision 6836\u20136846 (2021).","DOI":"10.1109\/ICCV48922.2021.00676"},{"key":"54981_CR48","doi-asserted-by":"crossref","unstructured":"Girdhar, R. et al. Imagebind: One embedding space to bind them all. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition 15180\u201315190 (2023).","DOI":"10.1109\/CVPR52729.2023.01457"},{"key":"54981_CR49","doi-asserted-by":"publisher","first-page":"3132","DOI":"10.1109\/LSP.2025.3592113","volume":"32","author":"Y Liu","year":"2025","unstructured":"Liu, Y., Ma, Y., Qi, Y., Qing, L. & Li, G. Boosting uav detection via memory-enhanced attention and contrastive learning. IEEE Signal Process. Lett. 32, 3132\u20133136 (2025).","journal-title":"IEEE Signal Process. Lett."},{"key":"54981_CR50","unstructured":"Ma, Y., Qing, L., Li, G., Liu, Y., Qi, Y. & Huang, Q. Exploring the temporal consistency for point-level weakly-supervised temporal action localization. arXiv preprint arXiv:2602.05718 (2026)."},{"key":"54981_CR51","unstructured":"Ma, Y., Qing, L., Li, G., Liu, Y., Qi, Y. & Huang, Q. Boosting point-supervised temporal action localization via text refinement and alignment. arXiv preprint arXiv:2602.01257 (2026)."},{"key":"54981_CR52","doi-asserted-by":"crossref","unstructured":"Song, E., Chai, W., Wang, G., Zhang, Y., Zhou, H., Wu, F., Chi, H., Guo, X., Ye, T., Zhang, Y. et al. Moviechat: From dense token to sparse memory for long video understanding. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18221\u201318232 (2024).","DOI":"10.1109\/CVPR52733.2024.01725"},{"key":"54981_CR53","doi-asserted-by":"crossref","unstructured":"Zhu, Y. et al. Quantized gan for complex music generation from dance videos. In European Conference on Computer Vision 182\u2013199 Springer (2022).","DOI":"10.1007\/978-3-031-19836-6_11"},{"key":"54981_CR54","doi-asserted-by":"crossref","unstructured":"Li, R., Yang, S., Ross, D. A. & Kanazawa, A. Ai choreographer: Music conditioned 3d dance generation with aist. In Proceedings of the IEEE\/CVF International Conference on Computer Vision 13401\u201313412 (2021).","DOI":"10.1109\/ICCV48922.2021.01315"},{"key":"54981_CR55","unstructured":"Naeem, M. F., Oh, S. J., Uh, Y., Choi, Y. & Yoo, J. Reliable fidelity and diversity metrics for generative models. In International Conference on Machine Learning 7176\u20137185 (2020) (PMLR)."},{"key":"54981_CR56","doi-asserted-by":"crossref","unstructured":"Di, S., Jiang, Z., Liu, S., Wang, Z., Zhu, L., He, Z., Liu, H. & Yan, S. Video background music generation with controllable music transformer. In Proceedings of the 29th ACM International Conference on Multimedia, pp. 2037\u20132045 (2021).","DOI":"10.1145\/3474085.3475195"},{"key":"54981_CR57","unstructured":"Liu, S., Hussain, A. S., Wu, Q., Sun, C. & Shan, Y. M2ugen: Multi-modal music understanding and generation with the power of large language models (2023) arXiv:2311.11255 arXiv preprint."},{"key":"54981_CR58","doi-asserted-by":"crossref","unstructured":"Qin, Z., Yu, D., Luo, C. & Chen, Z. Sliced wasserstein bridge for open-vocabulary video instance segmentation. In Proceedings of the IEEE\/CVF International Conference on Computer Vision 12470\u201312478 (2025).","DOI":"10.1109\/ICCV51701.2025.01159"},{"issue":"5","key":"54981_CR59","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1109\/JAS.2023.123456","volume":"10","author":"Z Qin","year":"2023","unstructured":"Qin, Z. et al. Coarse-to-fine video instance segmentation with factorized conditional appearance flows. IEEE\/CAA J. Autom. Sin. 10(5), 1192\u20131208 (2023).","journal-title":"IEEE\/CAA J. Autom. Sin."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-54981-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-54981-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-54981-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T23:34:47Z","timestamp":1785886487000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-54981-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,26]]},"references-count":59,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["54981"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-54981-4","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,26]]},"assertion":[{"value":"13 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 May 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"24091"}}