{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:14:40Z","timestamp":1778692480978,"version":"3.51.4"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:00:00Z","timestamp":1778544000000},"content-version":"vor","delay-in-days":42,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EPJ Data Sci."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Community detection algorithms have become essential tools for accurately modeling real-world networks. In particular, the emergence of overlapping community detection techniques has made it possible to identify users\u2019 multiple affiliations, significantly enhancing the analysis of interpersonal relationships. However, this also raises serious privacy concerns, as some users or groups may not wish for their social relationships to be exposed via algorithmic inference. Although several community hiding methods have been proposed to address these issues, existing approaches typically overlook the inherently overlapping characteristics of communities, lack cross-scale adaptability, and exhibit limited interpretability. In this study, we propose a novel overlapping community hiding framework based on constrained graph adversarial training. By integrating trainable layers and a masking mechanism into the adversarial training process, our method effectively achieves multi-scale hiding of overlapping communities, while substantially improving the interpretability of the hiding process. To further enhance the effectiveness of the hiding process, we introduce a novel constraint strategy, termed SAG-NE, into graph adversarial training, which explicitly constrains node representations and symmetric approximate gradients within the same community, thereby increasing node dispersion in both feature and gradient spaces and making it significantly more difficult for existing detection algorithms to uncover the true community structures. Experimental results on multiple real-world and synthetic datasets demonstrate that the proposed framework exhibits robust privacy-preserving performance across different scales.<\/jats:p>","DOI":"10.1140\/epjds\/s13688-026-00645-2","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T08:37:10Z","timestamp":1774946230000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cross-scale overlapping community hiding via constrained graph adversarial training"],"prefix":"10.1140","volume":"15","author":[{"given":"Guoliang","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinlong","family":"Fei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,31]]},"reference":[{"key":"645_CR1","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1109\/SP.2010.21","volume-title":"2010 IEEE symposium on security and privacy","author":"G Wondracek","year":"2010","unstructured":"Wondracek G, Holz T, Kirda E, Kruegel C (2010) A practical attack to de-anonymize social network users. In: 2010 IEEE symposium on security and privacy, pp\u00a0223\u2013238"},{"issue":"3","key":"645_CR2","doi-asserted-by":"publisher","first-page":"3444","DOI":"10.1109\/TCSS.2023.3327810","volume":"11","author":"K Berahmand","year":"2024","unstructured":"Berahmand K, Li Y, Xu Y (2024) A deep semi-supervised community detection based on point-wise mutual information. IEEE Trans Comput Soc Syst 11(3):3444\u20133456","journal-title":"IEEE Trans Comput Soc Syst"},{"key":"645_CR3","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.90.012811","volume":"90","author":"S Sobolevsky","year":"2014","unstructured":"Sobolevsky S, Campari R (2014) General optimization technique for high-quality community detection in complex networks. Phys Rev E 90, Article ID 012811","journal-title":"Phys Rev E"},{"key":"645_CR4","doi-asserted-by":"publisher","first-page":"2486","DOI":"10.1109\/TVCG.2013.232","volume":"19","author":"C Vehlow","year":"2013","unstructured":"Vehlow C, Reinhardt T, Weiskopf D (2013) Visualizing fuzzy overlapping communities in networks. IEEE Trans Vis Comput Graph 19:2486\u20132495","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"645_CR5","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1140\/epjb\/e2011-10979-2","volume":"81","author":"L \u0160ubelj","year":"2011","unstructured":"\u0160ubelj L, Bajec M (2011) Robust network community detection using balanced propagation. Eur Phys J B 81:353\u2013362","journal-title":"Eur Phys J B"},{"key":"645_CR6","doi-asserted-by":"publisher","first-page":"3095","DOI":"10.1016\/j.physa.2013.03.014","volume":"392","author":"H Lou","year":"2013","unstructured":"Lou H, Li S, Zhao Y (2013) Detecting community structure using label propagation with weighted coherent neighborhood propinquity. Phys A 392:3095\u20133105","journal-title":"Phys A"},{"key":"645_CR7","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.83.036103","volume":"83","author":"L \u0160ubelj","year":"2011","unstructured":"\u0160ubelj L, Bajec M (2011) Unfolding communities in large complex networks: combining defensive and offensive label propagation for core extraction. Phys Rev E 83, Article ID 036103","journal-title":"Phys Rev E"},{"key":"645_CR8","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.69.026113","volume":"69","author":"MEJ Newman","year":"2004","unstructured":"Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69, Article ID 026113","journal-title":"Phys Rev E"},{"issue":"7","key":"645_CR9","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1109\/TMM.2015.2430819","volume":"17","author":"Q Fang","year":"2015","unstructured":"Fang Q, Sang J, Xu C, Hossain MS (2015) Relational user attribute inference in social media. IEEE Trans Multimed 17(7):1031\u20131044","journal-title":"IEEE Trans Multimed"},{"issue":"6","key":"645_CR10","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1109\/TMM.2016.2646181","volume":"19","author":"D Lu","year":"2017","unstructured":"Lu D, Sang J, Chen Z, Xu M, Mei T (2017) Who are your \u201creal\u201d friends: analyzing and distinguishing between offline and online friendships from social multimedia data. IEEE Trans Multimed 19(6):1299\u20131313","journal-title":"IEEE Trans Multimed"},{"key":"645_CR11","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/978-3-642-14527-8_15","volume-title":"Privacy enhancing technologies","author":"S Nagaraja","year":"2010","unstructured":"Nagaraja S (2010) The impact of unlinkability on adversarial community detection: effects and countermeasures. In: Atallah MJ, Hopper NJ (eds) Privacy enhancing technologies. Springer, Berlin, pp\u00a0253\u2013272"},{"issue":"4","key":"645_CR12","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1109\/TKDE.2017.2776133","volume":"30","author":"V Fionda","year":"2018","unstructured":"Fionda V, Pirr\u00f2 G (2018) Community deception or: how to stop fearing community detection algorithms. IEEE Trans Knowl Data Eng 30(4):660\u2013673","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"3","key":"645_CR13","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1109\/TCSS.2019.2912801","volume":"6","author":"J Chen","year":"2019","unstructured":"Chen J, Chen L, Chen Y, Zhao M, Yu S, Xuan Q, Yang X (2019) Ga-based q-attack on community detection. IEEE Trans Comput Soc Syst 6(3):491\u2013503","journal-title":"IEEE Trans Comput Soc Syst"},{"issue":"8","key":"645_CR14","first-page":"7693","volume":"35","author":"L Sun","year":"2023","unstructured":"Sun L, Dou Y, Yang C, Zhang K, Wang J, Yu PS, He L, Li B (2023) Adversarial attack and defense on graph data: a survey. IEEE Trans Knowl Data Eng 35(8):7693\u20137711","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"4","key":"645_CR15","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.78.046110","volume":"78","author":"A Lancichinetti","year":"2008","unstructured":"Lancichinetti A, Fortunato S, Radicchi F (2008) Benchmark graphs for testing community detection algorithms. Phys Rev E 78(4):6110","journal-title":"Phys Rev E"},{"issue":"7043","key":"645_CR16","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1038\/nature03607","volume":"435","author":"G Palla","year":"2005","unstructured":"Palla G, Der\u00e9nyi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(7043):814\u2013818","journal-title":"Nature"},{"key":"645_CR17","first-page":"615","volume-title":"Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining. KDD\u201912","author":"M Coscia","year":"2012","unstructured":"Coscia M, Rossetti G, Giannotti F, Pedreschi D (2012) Demon: a local-first discovery method for overlapping communities. In: Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining. KDD\u201912. Association for Computing Machinery, New York, pp\u00a0615\u2013623"},{"key":"645_CR18","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.procs.2019.04.010","volume":"151","author":"N Kasoro","year":"2019","unstructured":"Kasoro N, Kasereka S, Mayogha E, Vinh HT, Kinganga J (2019) Percomcv: a hybrid approach of community detection in social networks. Proc Comput Sci 151:45\u201352","journal-title":"Proc Comput Sci"},{"key":"645_CR19","doi-asserted-by":"crossref","unstructured":"Wu M, Li X, Kwoh C-K, Ng S-K (2009) A core-attachment based method to detect protein complexes in ppi networks. BMC Bioinform 10(169)","DOI":"10.1186\/1471-2105-10-169"},{"issue":"2","key":"645_CR20","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1038\/s41562-017-0290-3","volume":"2","author":"M Waniek","year":"2018","unstructured":"Waniek M, Michalak TP, Rahwan T, Wooldridge MJ (2018) Hiding individuals and communities in a social network. Nat Hum Behav 2(2):139\u2013147","journal-title":"Nat Hum Behav"},{"key":"645_CR21","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1007\/978-3-540-70600-7_25","volume-title":"International conference on bioinformatics research and development","author":"V Fionda","year":"2008","unstructured":"Fionda V, Palopoli L, Panni S, Rombo SE (2008) Protein-protein interaction network querying by a \u201cfocus and zoom\u201d approach. In: International conference on bioinformatics research and development, vol\u00a013. Springer, Berlin, pp\u00a0331\u2013346"},{"key":"645_CR22","doi-asserted-by":"crossref","unstructured":"Jin D, Yu Z, Jiao P, Pan S, He D, Wu J, Yu P, Zhang W (2021) A survey of community detection approaches: from statistical modeling to deep learning. IEEE Trans Knowl Data Eng, 1\u20131","DOI":"10.1109\/TKDE.2021.3104155"},{"key":"645_CR23","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1016\/j.physa.2006.07.023","volume":"374","author":"S Zhang","year":"2007","unstructured":"Zhang S, Wang R, Zhang X (2007) Identification of overlapping community structure in complex networks using fuzzy c-means clustering. Phys A 374:483\u2013490","journal-title":"Phys A"},{"key":"645_CR24","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.83.066114","volume":"83","author":"I Psorakis","year":"2011","unstructured":"Psorakis I, Roberts S, Ebden M, Sheldon B (2011) Overlapping community detection using Bayesian non-negative matrix factorization. Phys Rev E 83, Article ID 066114","journal-title":"Phys Rev E"},{"key":"645_CR25","doi-asserted-by":"publisher","first-page":"37261","DOI":"10.1109\/ACCESS.2018.2838568","volume":"6","author":"L Fan","year":"2018","unstructured":"Fan L, Xu S, Liu D, Ru Y (2018) Semi-supervised community detection based on distance dynamics. IEEE Access 6:37261\u201337271","journal-title":"IEEE Access"},{"key":"645_CR26","first-page":"274","volume-title":"International conference on advances in social networks analysis and mining. ASONAM 2012","author":"F Reid","year":"2012","unstructured":"Reid F, McDaid AF, Hurley NJ (2012) Percolation computation in complex networks. In: International conference on advances in social networks analysis and mining. ASONAM 2012. IEEE Computer Society, Istanbul, pp\u00a0274\u2013281"},{"issue":"7307","key":"645_CR27","doi-asserted-by":"publisher","DOI":"10.1038\/nature09182","volume":"466","author":"YY Ahn","year":"2010","unstructured":"Ahn YY, Bagrow JP, Lehmann S (2010) Link communities reveal multiscale complexity in networks. Nature 466(7307):761","journal-title":"Nature"},{"key":"645_CR28","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1109\/SPAC.2014.6982726","volume-title":"Proceedings 2014 IEEE international conference on security, pattern analysis, and cybernetics (SPAC)","author":"W Zhang","year":"2014","unstructured":"Zhang W, Guan N, Huang X, Luo Z, Li J (2014) Overlapping community detection via link partition of asymmetric weighted graph. In: Proceedings 2014 IEEE international conference on security, pattern analysis, and cybernetics (SPAC), pp\u00a0417\u2013422"},{"key":"645_CR29","doi-asserted-by":"publisher","first-page":"6578","DOI":"10.1016\/j.physa.2013.08.028","volume":"392","author":"W Wang","year":"2013","unstructured":"Wang W, Liu D, Liu X, Pan L (2013) Fuzzy overlapping community detection based on local random walk and multidimensional scaling. Phys A 392:6578\u20136586","journal-title":"Phys A"},{"key":"645_CR30","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1007\/s00500-012-0924-3","volume":"17","author":"B Fabricio","year":"2013","unstructured":"Fabricio B, Liang Z (2013) Fuzzy community structure detection by particle competition and cooperation. Soft Comput 17:659\u2013673","journal-title":"Soft Comput"},{"key":"645_CR31","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.77.016107","volume":"77","author":"T Nepusz","year":"2008","unstructured":"Nepusz T, Petr\u00f3czi A, N\u00e9gyessy L, Bazs\u00f3 F (2008) Fuzzy communities and the concept of bridgeness in complex networks. Phys Rev E 77, Article ID 016107","journal-title":"Phys Rev E"},{"key":"645_CR32","first-page":"816","volume-title":"2013 IEEE 4th international conference on software engineering and service science","author":"L Lv","year":"2013","unstructured":"Lv L, Yang W, Yang Y, Tan F (2013) Overlapping community detection algorithms in complex networks based on the fuzzy spectral clustering. In: 2013 IEEE 4th international conference on software engineering and service science, pp\u00a0816\u2013819"},{"issue":"C","key":"645_CR33","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.patrec.2015.11.008","volume":"70","author":"H Zhang","year":"2016","unstructured":"Zhang H, Chen X, Li J, Zhou B (2016) Fuzzy community detection via modularity guided membership-degree propagation. Pattern Recognit Lett 70(C):66\u201372","journal-title":"Pattern Recognit Lett"},{"key":"645_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2629511","volume":"9","author":"M Coscia","year":"2014","unstructured":"Coscia M, Rossetti G, Giannotti F, Pedreschi D (2014) Uncovering hierarchical and overlapping communities with a local-first approach. ACM Trans Knowl Discov Data 9:1\u201327","journal-title":"ACM Trans Knowl Discov Data"},{"key":"645_CR35","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1007\/978-3-030-36687-2_13","volume-title":"Complex networks and their applications VIII","author":"G Rossetti","year":"2020","unstructured":"Rossetti G (2020) Exorcising the demon: angel, efficient node-centric community discovery. In: Cherifi H, Gaito S, Mendes JF, Moro E, Rocha LM (eds) Complex networks and their applications VIII. Springer, Cham, pp\u00a0152\u2013163"},{"key":"645_CR36","series-title":"International world wide web conferences steering committee, republic and canton of Geneva, CHE","first-page":"658","volume-title":"Proceedings of the 24th international conference on world wide web. WWW\u201915","author":"Y Li","year":"2015","unstructured":"Li Y, He K, Bindel D, Hopcroft JE (2015) Uncovering the small community structure in large networks: a local spectral approach. In: Proceedings of the 24th international conference on world wide web. WWW\u201915. International world wide web conferences steering committee, republic and canton of Geneva, CHE, pp\u00a0658\u2013668"},{"key":"645_CR37","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1109\/ICDMW.2011.154","volume-title":"2011 IEEE 11th international conference on data mining workshops","author":"J Xie","year":"2011","unstructured":"Xie J, Szymanski BK, Liu X (2011) Slpa: uncovering overlapping communities in social networks via a speaker-listener interaction dynamic process. In: 2011 IEEE 11th international conference on data mining workshops, pp\u00a0344\u2013349"},{"issue":"9","key":"645_CR38","doi-asserted-by":"publisher","first-page":"1736","DOI":"10.1109\/TKDE.2018.2866424","volume":"31","author":"M Lu","year":"2019","unstructured":"Lu M, Zhang Z, Qu Z, Kang Y (2019) Lpanni: overlapping community detection using label propagation in large-scale complex networks. IEEE Trans Knowl Data Eng 31(9):1736\u20131749","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"645_CR39","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.comcom.2022.12.008","volume":"199","author":"S Yuan","year":"2023","unstructured":"Yuan S, Zeng H, Zuo Z, Wang C (2023) Overlapping community detection on complex networks with graph convolutional networks. Comput Commun 199:62\u201371","journal-title":"Comput Commun"},{"key":"645_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2024.107529","volume":"163","author":"K Sismanis","year":"2025","unstructured":"Sismanis K, Potikas P, Souliou D, Pagourtzis A (2025) Overlapping community detection using graph attention networks. Future Gener Comput Syst 163, Article ID 107529","journal-title":"Future Gener Comput Syst"},{"key":"645_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109495","volume":"253","author":"D Liu","year":"2022","unstructured":"Liu D, Chang Z, Yang G, Chen E (2022) Community hiding using a graph autoencoder. Knowl-Based Syst 253, Article ID 109495","journal-title":"Knowl-Based Syst"},{"issue":"8","key":"645_CR42","doi-asserted-by":"publisher","first-page":"4954","DOI":"10.1109\/TSMC.2023.3240765","volume":"53","author":"J Zhao","year":"2023","unstructured":"Zhao J, Wang Z, Cao J, Cheong KH (2023) A self-adaptive evolutionary deception framework for community structure. IEEE Trans Syst Man Cybern Syst 53(8):4954\u20134967","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"645_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120665","volume":"672","author":"Z Chang","year":"2024","unstructured":"Chang Z, Liang J, Ma S, Liu D (2024) Community hiding: completely escape from community detection. Inf Sci 672, Article ID 120665","journal-title":"Inf Sci"},{"key":"645_CR44","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1145\/3637528.3671896","volume-title":"Proceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining. KDD\u201924","author":"A Bernini","year":"2024","unstructured":"Bernini A, Silvestri F, Tolomei G (2024) Evading community detection via counterfactual neighborhood search. In: Proceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining. KDD\u201924. Association for Computing Machinery, New York, pp\u00a0131\u2013140"},{"key":"645_CR45","unstructured":"Silvestri M, Edoardo\u00a0Gabrielli FS, Tolomei G (2025) The right to hide: masking community affiliation via minimal graph rewiring. arXiv preprint. arXiv:2502.00432"},{"key":"645_CR46","unstructured":"Loi D, Matteo\u00a0Silvestri FS, Tolomei G (2025) Evading overlapping community detection via proxy node injection. arXiv preprint. arXiv:2509.21211"},{"key":"645_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120235","volume":"663","author":"D Liu","year":"2024","unstructured":"Liu D, Jia R, Liu X, Zhang W (2024) A unified framework of community hiding using symmetric nonnegative matrix factorization. Inf Sci 663, Article ID 120235","journal-title":"Inf Sci"},{"issue":"4","key":"645_CR48","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1109\/TCSS.2021.3062711","volume":"8","author":"S Mittal","year":"2021","unstructured":"Mittal S, Sengupta D, Chakraborty T (2021) Hide and seek: outwitting community detection algorithms. IEEE Trans Comput Soc Syst 8(4):799\u2013808","journal-title":"IEEE Trans Comput Soc Syst"}],"container-title":["EPJ Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1140\/epjds\/s13688-026-00645-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1140\/epjds\/s13688-026-00645-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1140\/epjds\/s13688-026-00645-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T16:28:10Z","timestamp":1778689690000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1140\/epjds\/s13688-026-00645-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,31]]},"references-count":48,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["645"],"URL":"https:\/\/doi.org\/10.1140\/epjds\/s13688-026-00645-2","relation":{},"ISSN":["2193-1127"],"issn-type":[{"value":"2193-1127","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,31]]},"assertion":[{"value":"25 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable. This study does not involve human participants, human data, or animal subjects.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"48"}}