{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T17:52:46Z","timestamp":1790358766243,"version":"4.1.0"},"reference-count":67,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T00:00:00Z","timestamp":1778803200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2024-04733"],"award-info":[{"award-number":["RGPIN-2024-04733"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing &amp; Management"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ipm.2026.104862","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T16:41:47Z","timestamp":1779122507000},"page":"104862","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"PB","title":["Diffusion-based generative modeling for expert team formation"],"prefix":"10.1016","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0065-0972","authenticated-orcid":false,"given":"Mohammad Hossein","family":"Saliminabi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1630-3938","authenticated-orcid":false,"given":"Sajad","family":"Ebrahimi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9044-3723","authenticated-orcid":false,"given":"Radin","family":"Hamidi Rad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4892-6324","authenticated-orcid":false,"given":"Dimitrios","family":"Androutsos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2102-9190","authenticated-orcid":false,"given":"Fattane","family":"Zarrinkalam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5148-6237","authenticated-orcid":false,"given":"Ebrahim","family":"Bagheri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2026.104862_b1","series-title":"Proceedings of the ACM SIGMOD international conference on management of data, SIGMOD 2013, New York, NY, USA, June 22\u201327, 2013","first-page":"349","article-title":"Fast exact shortest-path distance queries on large networks by pruned landmark labeling","author":"Akiba","year":"2013"},{"issue":"2\u20133","key":"10.1016\/j.ipm.2026.104862_b2","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1561\/1500000024","article-title":"Expertise retrieval","volume":"6","author":"Balog","year":"2012","journal-title":"Foundations and Trends in Information Retrieval"},{"key":"10.1016\/j.ipm.2026.104862_b3","series-title":"Proceedings of the eighteenth ACM international conference on web search and data mining, WSDM 2025, Hannover, Germany, March 10\u201314, 2025","first-page":"914","article-title":"Adaptive loss-based curricula for neural team recommendation","author":"Barzegar","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b4","series-title":"Forty-second international conference on machine learning","article-title":"Zero shot generalization of vision-based RL without data augmentation","author":"Batra","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b5","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2021.102791","article-title":"Guest editorial of the IPM special issue on algorithmic bias and fairness in search and recommendation","volume":"59","author":"Boratto","year":"2022","journal-title":"Information Processing & Management"},{"issue":"2","key":"10.1016\/j.ipm.2026.104862_b6","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2022.103208","article-title":"Practical perspectives of consumer fairness in recommendation","volume":"60","author":"Boratto","year":"2023","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104862_b7","series-title":"Proceedings of the 24th international conference on artificial intelligence and statistics","first-page":"3565","article-title":"Towards a theoretical understanding of the robustness of variational autoencoders","volume":"vol. 130","author":"Camuto","year":"2021"},{"issue":"3","key":"10.1016\/j.ipm.2026.104862_b8","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104070","article-title":"Incorporating forgetting curve and memory replay for evolving socially-aware recommendation","volume":"62","author":"Chen","year":"2025","journal-title":"Information Processing & Management"},{"issue":"6","key":"10.1016\/j.ipm.2026.104862_b9","first-page":"1","article-title":"On the opportunities and challenges of offline reinforcement learning for recommender systems","volume":"42","author":"Chen","year":"2024","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.ipm.2026.104862_b10","doi-asserted-by":"crossref","unstructured":"Choi, J., Kim, S., Jeong, Y., Gwon, Y., & Yoon, S. (2021). ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 14367\u201314376). http:\/\/dx.doi.org\/10.1109\/ICCV48922.2021.01410.","DOI":"10.1109\/ICCV48922.2021.01410"},{"key":"10.1016\/j.ipm.2026.104862_b11","doi-asserted-by":"crossref","first-page":"145687","DOI":"10.1109\/ACCESS.2020.3015017","article-title":"Team formation in software engineering: A systematic mapping study","volume":"8","author":"Costa","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.ipm.2026.104862_b12","series-title":"ECIR 2025, Lucca, Italy, April 6\u201310, 2025","first-page":"362","article-title":"Retrieval-augmented neural team formation","volume":"vol. 15574","author":"Dara","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b13","series-title":"ACM CIKM 2022, Atlanta, GA, USA, October 17\u201321, 2022","first-page":"3913","article-title":"OpeNTF: A benchmark library for neural team formation","author":"Dashti","year":"2022"},{"key":"10.1016\/j.ipm.2026.104862_b14","series-title":"NeurIPS 2021","article-title":"Diffusion models beat GANs on image synthesis","author":"Dhariwal","year":"2021"},{"issue":"10","key":"10.1016\/j.ipm.2026.104862_b15","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/j.datak.2011.06.004","article-title":"Interaction mining and skill-dependent recommendations for multi-objective team composition","volume":"70","author":"Dorn","year":"2011","journal-title":"Data & Knowledge Engineering"},{"issue":"4","key":"10.1016\/j.ipm.2026.104862_b16","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/TKDE.2019.2893361","article-title":"GERF: A group event recommendation framework based on learning-to-rank","volume":"32","author":"Du","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"2","key":"10.1016\/j.ipm.2026.104862_b17","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1080\/10618600.2022.2070171","article-title":"Integrated depths for partially observed functional data","volume":"32","author":"El\u00edas","year":"2023","journal-title":"Journal of Computational and Graphical Statistics"},{"key":"10.1016\/j.ipm.2026.104862_b18","series-title":"Advances in information retrieval: 46th European conference on information retrieval, ECIR 2024, Glasgow, UK, March 24\u201328, 2024, proceedings, part I","first-page":"325","article-title":"A streaming approach to&nbsp;neural team formation training","author":"Fani","year":"2024"},{"key":"10.1016\/j.ipm.2026.104862_b19","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125971","article-title":"Peer review expert group recommendation: A multi-subject coverage-based approach","volume":"264","author":"Fu","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.ipm.2026.104862_b20","series-title":"ACM SIGIR 2021, virtual event, Canada, July 11\u201315, 2021","first-page":"2015","article-title":"Retrieving skill-based teams from collaboration networks","author":"Hamidi Rad","year":"2021"},{"key":"10.1016\/j.ipm.2026.104862_b21","series-title":"ACM webSci \u201922, Barcelona, Spain, June 26 \u2013 29, 2022","first-page":"148","article-title":"Subgraph representation learning for team mining","author":"Hamidi Rad","year":"2022"},{"issue":"3","key":"10.1016\/j.ipm.2026.104862_b22","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1145\/3735650","article-title":"Robust neural model for searching over incomplete graphs","volume":"17","author":"Hamidi Rad","year":"2026","journal-title":"ACM Trans. Intell. Syst. Technol."},{"issue":"1","key":"10.1016\/j.ipm.2026.104862_b23","doi-asserted-by":"crossref","DOI":"10.1145\/3589762","article-title":"A variational neural architecture for skill-based team formation","volume":"42","author":"Hamidi Rad","year":"2023","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.ipm.2026.104862_b24","series-title":"CIKM \u201920: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020","first-page":"2049","article-title":"Learning to form skill-based teams of experts","author":"Hamidi Rad","year":"2020"},{"issue":"1","key":"10.1016\/j.ipm.2026.104862_b25","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1007\/s10791-023-09421-6","article-title":"Learning heterogeneous subgraph representations for team discovery","volume":"26","author":"Hamidi Rad","year":"2023","journal-title":"Inf. Retr. J."},{"key":"10.1016\/j.ipm.2026.104862_b26","series-title":"EDBT 2022, Edinburgh, UK, March 29 \u2013 April 1, 2022","first-page":"2:440","article-title":"A neural approach to forming coherent teams in collaboration networks","author":"Hamidi Rad","year":"2022"},{"key":"10.1016\/j.ipm.2026.104862_b27","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 770\u2013778). http:\/\/dx.doi.org\/10.1109\/CVPR.2016.90.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.ipm.2026.104862_b28","series-title":"ACM SIGIR 2024, Washington DC, USA, July 14\u201318, 2024","first-page":"1172","article-title":"LADy: A benchmark toolkit for latent aspect detection enriched with backtranslation augmentation","author":"Hemmatizadeh","year":"2024"},{"key":"10.1016\/j.ipm.2026.104862_b29","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"vol. 33","author":"Ho","year":"2020"},{"key":"10.1016\/j.ipm.2026.104862_b30","first-page":"3085","article-title":"Reconstructing diffusion networks from incomplete data","volume":"vol. 2022","author":"Huang","year":"2022"},{"issue":"2","key":"10.1016\/j.ipm.2026.104862_b31","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/MCI.2022.3155327","article-title":"Hands-on Bayesian neural networks\u2014A tutorial for deep learning users","volume":"17","author":"Jospin","year":"2022","journal-title":"IEEE Computational Intelligence Magazine"},{"key":"10.1016\/j.ipm.2026.104862_b32","series-title":"ACM CIKM 2011, Glasgow, United kingdom, October 24\u201328, 2011","first-page":"985","article-title":"Discovering top-k teams of experts with\/without a leader in social networks","author":"Kargar","year":"2011"},{"issue":"10","key":"10.1016\/j.ipm.2026.104862_b33","doi-asserted-by":"crossref","first-page":"681","DOI":"10.14778\/2021017.2021025","article-title":"Keyword search in graphs: Finding r-cliques","volume":"4","author":"Kargar","year":"2011","journal-title":"Proceedings of VLDB Endowment"},{"key":"10.1016\/j.ipm.2026.104862_b34","series-title":"Machine learning and knowledge discovery in databases - European conference, ECML PKDD 2012, Bristol, UK, September 24\u201328, 2012. proceedings, part II","first-page":"483","article-title":"Efficient bi-objective team formation in social networks","volume":"vol. 7524","author":"Kargar","year":"2012"},{"issue":"2","key":"10.1016\/j.ipm.2026.104862_b35","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1109\/TKDE.2020.2985376","article-title":"Effective keyword search over weighted graphs","volume":"34","author":"Kargar","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.ipm.2026.104862_b36","series-title":"Complex networks and their applications VIII - volume 2 proceedings of the eighth international conference on complex networks and their applications COMPLEX NETWORKS 2019, Lisbon, Portugal, December 10\u201312, 2019","first-page":"995","article-title":"Using machine learning to predict links and improve steiner tree solutions to team formation problems","volume":"vol. 882","author":"Keane","year":"2019"},{"key":"10.1016\/j.ipm.2026.104862_b37","series-title":"NeurIPS 2017, December 4\u20139, 2017, Long Beach, CA, USA","first-page":"6348","article-title":"Learning combinatorial optimization algorithms over graphs","author":"Khalil","year":"2017"},{"issue":"2","key":"10.1016\/j.ipm.2026.104862_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2019.102054","article-title":"Compact group discovery in attributed graphs and social networks","volume":"57","author":"Khan","year":"2020","journal-title":"Information Processing & Management"},{"issue":"12","key":"10.1016\/j.ipm.2026.104862_b39","doi-asserted-by":"crossref","first-page":"12495","DOI":"10.1007\/s10115-025-02601-4","article-title":"Learning to rank under uncertainty: a robust neural approach","volume":"67","author":"Khodabakhsh","year":"2025","journal-title":"Knowledge and Information Systems"},{"key":"10.1016\/j.ipm.2026.104862_b40","article-title":"Auto-encoding variational Bayes","author":"Kingma","year":"2013","journal-title":"CoRR"},{"key":"10.1016\/j.ipm.2026.104862_b41","series-title":"ACM SIGKDD, Paris, France, June 28 \u2013 July 1, 2009","first-page":"447","article-title":"Collaborative filtering with temporal dynamics","author":"Koren","year":"2009"},{"key":"10.1016\/j.ipm.2026.104862_b42","series-title":"KDD","first-page":"467","article-title":"Finding a team of experts in social networks","author":"Lappas","year":"2009"},{"key":"10.1016\/j.ipm.2026.104862_b43","unstructured":"Le, Q., & Mikolov, T. (2014). Distributed Representations of Sentences and Documents. In Proceedings of the 31st international conference on machine learning."},{"key":"10.1016\/j.ipm.2026.104862_b44","series-title":"Proceedings of the 31st ACM SIGKDD conference on knowledge discovery and data mining v.2","first-page":"6074","article-title":"Diffusion models for recommender systems: From content distribution to content creation","author":"Lin","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b45","series-title":"CVPR","first-page":"11461","article-title":"Repaint: Inpainting using denoising diffusion probabilistic models","author":"Lugmayr","year":"2022"},{"key":"10.1016\/j.ipm.2026.104862_b46","series-title":"ICLR","article-title":"SDEdit: Guided image synthesis and editing with stochastic differential equations","author":"Meng","year":"2022"},{"key":"10.1016\/j.ipm.2026.104862_b47","series-title":"Forty-second international conference on machine learning","article-title":"I think, therefore I diffuse: Enabling multimodal in-context reasoning in diffusion models","author":"Mi","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b48","series-title":"1st international conference on learning representations, ICLR 2013, Scottsdale, Arizona, USA, May 2\u20134, 2013, workshop track proceedings","article-title":"Efficient estimation of word representations in vector space","author":"Mikolov","year":"2013"},{"key":"10.1016\/j.ipm.2026.104862_b49","series-title":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022","first-page":"4936","article-title":"PyDHNet: A python library for dynamic heterogeneous network representation learning and evaluation","author":"Nguyen","year":"2022"},{"key":"10.1016\/j.ipm.2026.104862_b50","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.119371","article-title":"DyHNet: Learning dynamic heterogeneous network representations","volume":"646","author":"Nguyen","year":"2023","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ipm.2026.104862_b51","series-title":"International conference on machine learning","first-page":"8162","article-title":"Improved denoising diffusion probabilistic models","author":"Nichol","year":"2021"},{"key":"10.1016\/j.ipm.2026.104862_b52","series-title":"Missdiff: Training diffusion models on tabular data with missing values","author":"Ouyang","year":"2023"},{"key":"10.1016\/j.ipm.2026.104862_b53","doi-asserted-by":"crossref","DOI":"10.1016\/j.infsof.2022.107066","article-title":"Memorization and generalization in neural code intelligence models","volume":"153","author":"Rabin","year":"2023","journal-title":"Information and Software Technology"},{"key":"10.1016\/j.ipm.2026.104862_b54","series-title":"MICCAI 2015, Munich, Germany, October 5\u20139, 2015, proceedings, part III 18","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"issue":"1","key":"10.1016\/j.ipm.2026.104862_b55","first-page":"1","article-title":"Deep neural networks for optimal team composition","volume":"2","author":"Sapienza","year":"2019","journal-title":"Frontiers in Big Data"},{"key":"10.1016\/j.ipm.2026.104862_b56","series-title":"ICML","first-page":"2256","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","author":"Sohl-Dickstein","year":"2015"},{"key":"10.1016\/j.ipm.2026.104862_b57","series-title":"ICLR","article-title":"Score-based generative modeling through stochastic differential equations","author":"Song","year":"2021"},{"key":"10.1016\/j.ipm.2026.104862_b58","series-title":"ACM SIGKDD 2010, Washington, DC, USA, July 25\u201328, 2010","first-page":"939","article-title":"The community-search problem and how to plan a successful cocktail party","author":"Sozio","year":"2010"},{"key":"10.1016\/j.ipm.2026.104862_b59","series-title":"Proceedings of the 48th international ACM SIGIR conference on research and development in information retrieval, SIGIR 2025, Padua, Italy, July 13\u201318, 2025","first-page":"2800","article-title":"Translative neural team recommendation: From multilabel classification to sequence prediction","author":"Thang","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b60","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"NeurIPS"},{"issue":"7","key":"10.1016\/j.ipm.2026.104862_b61","doi-asserted-by":"crossref","first-page":"6936","DOI":"10.1109\/TCSVT.2025.3532309","article-title":"Graph convolutional mixture-of-experts learner network for long-tailed domain generalization","volume":"35","author":"Wang","year":"2025","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.ipm.2026.104862_b62","series-title":"Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval","first-page":"832","article-title":"Diffusion recommender model","author":"Wang","year":"2023"},{"key":"10.1016\/j.ipm.2026.104862_b63","series-title":"WSDM","article-title":"Recurrent recommender networks","author":"Wu","year":"2017"},{"issue":"4","key":"10.1016\/j.ipm.2026.104862_b64","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103731","article-title":"Limits of predictability in top-N recommendation","volume":"61","author":"Xu","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104862_b65","doi-asserted-by":"crossref","unstructured":"Zhang, L., Hamidi Rad, R., Zihayat, M., & Bagheri, E. (2025). Say the Task, Build the Team: Prompt-Based Team Formation. In Lecture notes in computer science, Proceedings of the 17th international conference on advances in social networks analysis and mining (ASONAM 2025). Niagara Falls, ON, Canada.","DOI":"10.1007\/978-3-032-13513-1_19"},{"key":"10.1016\/j.ipm.2026.104862_b66","series-title":"Incomplete data, complete dynamics: A diffusion approach","author":"Zhou","year":"2025"},{"key":"10.1016\/j.ipm.2026.104862_b67","series-title":"EDBT \u201917","first-page":"498","article-title":"Authority-based team discovery in social networks","author":"Zihayat","year":"2017"}],"container-title":["Information Processing &amp; Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326002530?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326002530?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T14:39:25Z","timestamp":1783694365000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326002530"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":67,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S0306457326002530"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104862","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Diffusion-based generative modeling for expert team formation","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104862","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"104862"}}