{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T12:29:49Z","timestamp":1771504189697,"version":"3.50.1"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006690","name":"Politecnico di Milano","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006690","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Quantum Mach. Intell."],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s42484-026-00341-4","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T11:46:40Z","timestamp":1771501600000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Minor embedding for quantum annealing with reinforcement learning"],"prefix":"10.1007","volume":"8","author":[{"given":"Riccardo","family":"Nembrini","sequence":"first","affiliation":[]},{"given":"Maurizio","family":"Ferrari Dacrema","sequence":"additional","affiliation":[]},{"given":"Paolo","family":"Cremonesi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,2,19]]},"reference":[{"key":"341_CR1","doi-asserted-by":"crossref","unstructured":"Bernal DE, Booth KE, Dridi R, et al (2020) Integer programming techniques for minor-embedding in quantum annealers. In: Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 17th International Conference, CPAIOR 2020, Vienna, Austria, September 21\u201324, 2020, Proceedings 17, Springer, pp 112\u2013129","DOI":"10.1007\/978-3-030-58942-4_8"},{"issue":"1","key":"341_CR2","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s11128-015-1150-6","volume":"15","author":"T Boothby","year":"2016","unstructured":"Boothby T, King AD, Roy A (2016) Fast clique minor generation in chimera qubit connectivity graphs. Quantum Inf Process 15(1):495\u2013508. https:\/\/doi.org\/10.1007\/s11128-015-1150-6","journal-title":"Quantum Inf Process"},{"issue":"3","key":"341_CR3","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/BF01343193","volume":"51","author":"M Born","year":"1928","unstructured":"Born M, Fock V (1928) Beweis des adiabatensatzes Zeitschrift f\u00fcr Physik 51(3):165\u2013180. https:\/\/doi.org\/10.1007\/BF01343193","journal-title":"Beweis des adiabatensatzes Zeitschrift f\u00fcr Physik"},{"key":"341_CR4","unstructured":"Cai J, Macready WG, Roy A (2014) A practical heuristic for finding graph minors. CoRR abs\/1406.2741. http:\/\/arxiv.org\/abs\/1406.2741"},{"issue":"1","key":"341_CR5","doi-asserted-by":"publisher","first-page":"6539","DOI":"10.1038\/s41598-022-10169-0","volume":"12","author":"C Carugno","year":"2022","unstructured":"Carugno C, Ferrari Dacrema M, Cremonesi P (2022) Evaluating the job shop scheduling problem on a d-wave quantum annealer. Nat Sci Rep 12(1):6539\u2013655. https:\/\/doi.org\/10.1038\/s41598-022-10169-0","journal-title":"Nat Sci Rep"},{"key":"341_CR6","doi-asserted-by":"publisher","unstructured":"Carugno C, Ferrari Dacrema M, Cremonesi P (2024) Adaptive learning for quantum linear regression. In: Osinski M, Cour BL, Yeh L (eds) IEEE International Conference on Quantum Computing and Engineering, QCE 2024, Montreal, QC, Canada, September 15-20, 2024. IEEE, pp 1595\u20131599,https:\/\/doi.org\/10.1109\/QCE60285.2024.00186","DOI":"10.1109\/QCE60285.2024.00186"},{"key":"341_CR7","doi-asserted-by":"publisher","unstructured":"Chiavassa P, Marchesin A, Pedone I, et al (2022) Virtual network function embedding with quantum annealing. In: (ed) IEEE International Conference on Quantum Computing and Engineering, QCE 2022, Broomfield, CO, USA, September 18-23, 2022. IEEE, pp 282\u2013291,https:\/\/doi.org\/10.1109\/QCE53715.2022.00048","DOI":"10.1109\/QCE53715.2022.00048"},{"issue":"7","key":"341_CR8","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/s11128-020-02681-x","volume":"19","author":"YL Fang","year":"2020","unstructured":"Fang YL, Warburton P (2020) Minimizing minor embedding energy: an application in quantum annealing. Quantum Inf Process 19(7):191","journal-title":"Quantum Inf Process"},{"key":"341_CR9","unstructured":"Farhi E, Goldstone J, Gutmann S, et al (2000) Quantum computation by adiabatic evolution. arXiv preprint quant-ph\/0001106"},{"key":"341_CR10","doi-asserted-by":"publisher","unstructured":"Ferrari Dacrema M, Moroni F, Nembrini R, et al (2022) Towards feature selection for ranking and classification exploiting quantum annealers. In: Amig\u00f3 E, Castells P, Gonzalo J, et al (eds) SIGIR \u201922: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022. ACM, pp 2814\u20132824, https:\/\/doi.org\/10.1145\/3477495.3531755","DOI":"10.1145\/3477495.3531755"},{"key":"341_CR11","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s10479-022-04634-2","volume":"314","author":"F Glover","year":"2022","unstructured":"Glover F, Kochenberger G, Hennig R et al (2022) Quantum bridge analytics i: a tutorial on formulating and using qubo models. Ann Oper Res 314:141\u2013183. https:\/\/doi.org\/10.1007\/s10479-022-04634-2","journal-title":"Ann Oper Res"},{"issue":"6","key":"341_CR12","doi-asserted-by":"publisher","first-page":"1291","DOI":"10.1109\/TSMCC.2012.2218595","volume":"42","author":"I Grondman","year":"2012","unstructured":"Grondman I, Busoniu L, Lopes GAD et al (2012) A survey of actor-critic reinforcement learning: Standard and natural policy gradients. IEEE Trans Syst Man Cybern Part C 42(6):1291\u20131307. https:\/\/doi.org\/10.1109\/TSMCC.2012.2218595","journal-title":"IEEE Trans Syst Man Cybern Part C"},{"issue":"5","key":"341_CR13","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s11128-017-1586-y","volume":"16","author":"M Hernandez","year":"2017","unstructured":"Hernandez M, Aramon M (2017) Enhancing quantum annealing performance for the molecular similarity problem. Quantum Inf Process 16(5):133. https:\/\/doi.org\/10.1007\/s11128-017-1586-y","journal-title":"Quantum Inf Process"},{"key":"341_CR14","doi-asserted-by":"publisher","unstructured":"Huang S, Onta\u00f1\u00f3n S (2022) A closer look at invalid action masking in policy gradient algorithms. In: Bart\u00e1k R, Keshtkar F, Franklin M (eds) Proceedings of the Thirty-Fifth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2022, Hutchinson Island, Jensen Beach, Florida, USA, May 15-18, 2022, https:\/\/doi.org\/10.32473\/flairs.v35i.130584","DOI":"10.32473\/flairs.v35i.130584"},{"key":"341_CR15","doi-asserted-by":"publisher","first-page":"12837","DOI":"10.1038\/s41598-019-49172-3","volume":"9","author":"K Ikeda","year":"2019","unstructured":"Ikeda K, Nakamura Y, Humble TS (2019) Application of quantum annealing to nurse scheduling problem. Sci Rep 9:12837. https:\/\/doi.org\/10.1038\/s41598-019-49172-3","journal-title":"Sci Rep"},{"issue":"7346","key":"341_CR16","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1038\/nature10012","volume":"473","author":"MW Johnson","year":"2011","unstructured":"Johnson MW, Amin MH, Gildert S et al (2011) Quantum annealing with manufactured spins. Nature 473(7346):194\u2013198","journal-title":"Nature"},{"key":"341_CR17","doi-asserted-by":"publisher","first-page":"5355","DOI":"10.1103\/PhysRevE.58.5355","volume":"58","author":"T Kadowaki","year":"1998","unstructured":"Kadowaki T, Nishimori H (1998) Quantum annealing in the transverse ising model. Phys Rev E 58:5355\u20135363. https:\/\/doi.org\/10.1103\/PhysRevE.58.5355","journal-title":"Phys Rev E"},{"key":"341_CR18","unstructured":"Konda VR, Tsitsiklis JN (1999) Actor-critic algorithms. In: Solla SA, Leen TK, M\u00fcller K (eds) Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]. The MIT Press, pp 1008\u20131014, http:\/\/papers.nips.cc\/paper\/1786-actor-critic-algorithms"},{"issue":"2","key":"341_CR19","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s11128-017-1809-2","volume":"17","author":"V Kumar","year":"2018","unstructured":"Kumar V, Bass G, Tomlin C et al (2018) Quantum annealing for combinatorial clustering. Quantum Inf Process 17(2):39. https:\/\/doi.org\/10.1007\/s11128-017-1809-2","journal-title":"Quantum Inf Process"},{"key":"341_CR20","doi-asserted-by":"publisher","first-page":"5","DOI":"10.3389\/fphy.2014.00005","volume":"2","author":"A Lucas","year":"2014","unstructured":"Lucas A (2014) Ising formulations of many np problems. Frontiers in physics 2:5","journal-title":"Frontiers in physics"},{"key":"341_CR21","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.94.022337","volume":"94","author":"S Mandr\u00e1","year":"2016","unstructured":"Mandr\u00e1 S, Zhu Z, Wang W et al (2016) Strengths and weaknesses of weak-strong cluster problems: A detailed overview of state-of-the-art classical heuristics versus quantum approaches. Phys Rev A 94:022337. https:\/\/doi.org\/10.1103\/PhysRevA.94.022337","journal-title":"Phys Rev A"},{"key":"341_CR22","doi-asserted-by":"publisher","first-page":"080501","DOI":"10.1103\/PhysRevLett.127.080501","volume":"127","author":"C Micheletti","year":"2021","unstructured":"Micheletti C, Hauke P, Faccioli P (2021) Polymer physics by quantum computing. Phys Rev Lett 127:080501. https:\/\/doi.org\/10.1103\/PhysRevLett.127.080501","journal-title":"Phys Rev Lett"},{"key":"341_CR23","unstructured":"Mnih V, Badia AP, Mirza M, et al (2016) Asynchronous methods for deep reinforcement learning. In: Balcan M, Weinberger KQ (eds) Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, JMLR Workshop and Conference Proceedings, vol\u00a048. JMLR.org, pp 1928\u20131937, http:\/\/proceedings.mlr.press\/v48\/mniha16.html"},{"key":"341_CR24","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1038\/nature24047","volume":"550","author":"A Mott","year":"2017","unstructured":"Mott A, Job J, Vlimant JR et al (2017) Solving a higgs optimization problem with quantum annealing for machine learning. Nature 550:375\u2013379. https:\/\/doi.org\/10.1038\/nature24047","journal-title":"Nature"},{"issue":"8","key":"341_CR25","doi-asserted-by":"publisher","first-page":"970","DOI":"10.3390\/e23080970","volume":"23","author":"R Nembrini","year":"2021","unstructured":"Nembrini R, Ferrari Dacrema M, Cremonesi P (2021) Feature selection for recommender systems with quantum computing. Entropy 23(8):970. https:\/\/doi.org\/10.3390\/e23080970","journal-title":"Entropy"},{"key":"341_CR26","doi-asserted-by":"publisher","unstructured":"Nembrini R, Carugno C, Ferrari Dacrema M, et al (2022) Towards recommender systems with community detection and quantum computing. In: Golbeck J, Harper FM, Murdock V, et al (eds) RecSys \u201922: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18 - 23, 2022. ACM, pp 579\u2013585, https:\/\/doi.org\/10.1145\/3523227.3551478","DOI":"10.1145\/3523227.3551478"},{"key":"341_CR27","unstructured":"Nembrini R, Ferrari Dacrema M, Cremonesi P (2024) An application of reinforcement learning for minor embedding in quantum annealing. In: Baioletti M, Gonz\u00e1lez M\u00c1, Oddi A, et al (eds) Proceedings of the International Workshop on AI for Quantum and Quantum for AI (AIQxQIA 2024) co-located with 23rd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2024), November 25 - November 28, 2024, Free University of Bolzano, Bolzano, Italy, CEUR Workshop Proceedings, vol 3913. CEUR-WS.org, https:\/\/ceur-ws.org\/Vol-3913\/short2.pdf"},{"key":"341_CR28","doi-asserted-by":"publisher","first-page":"55","DOI":"10.3389\/fphy.2018.00055","volume":"6","author":"F Neukart","year":"2018","unstructured":"Neukart F, Dollen DV, Seidel C (2018) Quantum-assisted cluster analysis on a quantum annealing device. Frontiers in Physics 6:55. https:\/\/doi.org\/10.3389\/fphy.2018.00055","journal-title":"Frontiers in Physics"},{"key":"341_CR29","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3389\/fphy.2017.00071","volume":"5","author":"F Neukart","year":"2018","unstructured":"Neukart F, Von Dollen D, Seidel C et al (2018) Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces. Frontiers in Physics 5:71. https:\/\/doi.org\/10.3389\/fphy.2017.00071","journal-title":"Frontiers in Physics"},{"key":"341_CR30","unstructured":"Neven H, Denchev VS, Rose G, et al (2009) Training a large scale classifier with the quantum adiabatic algorithm. CoRR abs\/0912.0779. http:\/\/arxiv.org\/abs\/0912.0779"},{"issue":"1","key":"341_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3763244","volume":"7","author":"H Ngo","year":"2025","unstructured":"Ngo H, Do N, Vu M et al (2025) Charme: A chain-based reinforcement learning approach for the minor embedding problem. ACM Transactions on Quantum Computing 7(1):1\u201328. https:\/\/doi.org\/10.1145\/3763244","journal-title":"ACM Transactions on Quantum Computing"},{"key":"341_CR32","doi-asserted-by":"publisher","unstructured":"Ngo HM, Kahveci T, Thai MT (2023) ATOM: an efficient topology adaptive algorithm for minor embedding in quantum computing. In: IEEE International Conference on Communications, ICC 2023, Rome, Italy, May 28 - June 1, 2023. IEEE, pp 2692\u20132697. https:\/\/doi.org\/10.1109\/ICC45041.2023.10279010","DOI":"10.1109\/ICC45041.2023.10279010"},{"key":"341_CR33","doi-asserted-by":"crossref","unstructured":"Ohzeki M (2020) Breaking limitation of quantum annealer in solving optimization problems under constraints. CoRR abs\/2002.05298. https:\/\/arxiv.org\/abs\/2002.05298","DOI":"10.1038\/s41598-020-60022-5"},{"key":"341_CR34","unstructured":"O\u2019Malley D, Vesselinov VV, Alexandrov BS, et al (2017) Nonnegative\/binary matrix factorization with a d-wave quantum annealer. CoRR abs\/1704.01605. http:\/\/arxiv.org\/abs\/1704.01605,"},{"key":"341_CR35","unstructured":"Ottaviani D, Amendola A (2018) Low rank non-negative matrix factorization with d-wave 2000q. https:\/\/doi.org\/10.48550\/arXiv.1808.08721, [quant-ph]"},{"key":"341_CR36","doi-asserted-by":"publisher","unstructured":"Pasin A, Ferrari Dacrema M, Cremonesi P, et al (2024) Overview of QuantumCLEF 2024: The quantum computing challenge for information retrieval and recommender systems at CLEF. In: Goeuriot L, Mulhem P, Qu\u00e9not G, et al (eds) Experimental IR Meets Multilinguality, Multimodality, and Interaction - 15th International Conference of the CLEF Association, CLEF 2024, Grenoble, France, September 9-12, 2024, Proceedings, Part II, Lecture Notes in Computer Science, vol 14959. Springer, pp 260\u2013282, https:\/\/doi.org\/10.1007\/978-3-031-71908-0_12","DOI":"10.1007\/978-3-031-71908-0_12"},{"issue":"2","key":"341_CR37","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/S42484-024-00179-8","volume":"6","author":"R Pellini","year":"2024","unstructured":"Pellini R, Ferrari Dacrema M (2024) Analyzing the effectiveness of quantum annealing with meta-learning. Quantum Machine Intelligence 6(2):48. https:\/\/doi.org\/10.1007\/S42484-024-00179-8","journal-title":"Quantum Machine Intelligence"},{"issue":"3","key":"341_CR38","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevApplied.21.034023","volume":"21","author":"E Pelofske","year":"2024","unstructured":"Pelofske E (2024) 4-clique network minor embedding for quantum annealers. Phys Rev Appl 21(3):034023","journal-title":"Phys Rev Appl"},{"key":"341_CR39","unstructured":"Raffin A, Hill A, Gleave A, et al (2021) Stable-baselines3: Reliable reinforcement learning implementations. Journal of Machine Learning Research 22(268):1\u20138. http:\/\/jmlr.org\/papers\/v22\/20-1364.html"},{"issue":"1","key":"341_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11128-014-0892-x","volume":"14","author":"EG Rieffel","year":"2015","unstructured":"Rieffel EG, Venturelli D, O\u2019Gorman B et al (2015) A case study in programming a quantum annealer for hard operational planning problems. Quantum Inf Process 14(1):1\u201336. https:\/\/doi.org\/10.1007\/s11128-014-0892-x","journal-title":"Quantum Inf Process"},{"key":"341_CR41","unstructured":"Schulman J, Levine S, Abbeel P, et al (2015) Trust region policy optimization. In: Bach FR, Blei DM (eds) Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, JMLR Workshop and Conference Proceedings, vol\u00a037. JMLR.org, pp 1889\u20131897, http:\/\/proceedings.mlr.press\/v37\/schulman15.html"},{"key":"341_CR42","unstructured":"Schulman J, Wolski F, Dhariwal P, et al (2017) Proximal policy optimization algorithms. CoRR abs\/1707.06347. http:\/\/arxiv.org\/abs\/1707.06347,"},{"key":"341_CR43","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1186\/s40537-019-0197-0","volume":"6","author":"C Shorten","year":"2019","unstructured":"Shorten C, Khoshgoftaar TM (2019) A survey on image data augmentation for deep learning. J Big Data 6:60. https:\/\/doi.org\/10.1186\/s40537-019-0197-0","journal-title":"J Big Data"},{"issue":"7587","key":"341_CR44","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1038\/nature16961","volume":"529","author":"D Silver","year":"2016","unstructured":"Silver D, Huang A, Maddison CJ et al (2016) Mastering the game of go with deep neural networks and tree search. Nature 529(7587):484\u2013489. https:\/\/doi.org\/10.1038\/nature16961","journal-title":"Nature"},{"issue":"6419","key":"341_CR45","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1126\/science.aar6404","volume":"362","author":"D Silver","year":"2018","unstructured":"Silver D, Hubert T, Schrittwieser J et al (2018) A general reinforcement learning algorithm that masters chess, shogi, and go through self-play. Science 362(6419):1140\u20131144. https:\/\/doi.org\/10.1126\/science.aar6404","journal-title":"Science"},{"key":"341_CR46","doi-asserted-by":"publisher","unstructured":"Stollenwerk T, Lobe E, Jung M (2017) Flight gate assignment with a quantum annealer. In: Feld S, Linnhoff-Popien C (eds) Quantum Technology and Optimization Problems - First International Workshop, QTOP@NetSys 2019, Munich, Germany, March 18, 2019, Proceedings, Lecture Notes in Computer Science, vol 11413. Springer, pp 99\u2013110, https:\/\/doi.org\/10.1007\/978-3-030-14082-3_9","DOI":"10.1007\/978-3-030-14082-3_9"},{"key":"341_CR47","doi-asserted-by":"publisher","unstructured":"Streif M, Neukart F, Leib M (2019) Solving quantum chemistry problems with a d-wave quantum annealer. https:\/\/doi.org\/10.48550\/arXiv.1811.05256, arXiv:1811.05256, [quant-ph]","DOI":"10.48550\/arXiv.1811.05256"},{"key":"341_CR48","unstructured":"Sutton RS, Barto AG (2018) Reinforcement learning - an introduction, 2nd Edition. MIT Press, http:\/\/www.incompleteideas.net\/book\/the-book-2nd.html"},{"key":"341_CR49","unstructured":"Towers M, Kwiatkowski A, Terry J, et al (2024) Gymnasium: A standard interface for reinforcement learning environments. arXiv preprint arXiv:2407.17032"},{"issue":"4","key":"341_CR50","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.92.042310","volume":"92","author":"W Vinci","year":"2015","unstructured":"Vinci W, Albash T, Paz-Silva G et al (2015) Quantum annealing correction with minor embedding. Phys Rev A 92(4):042310","journal-title":"Phys Rev A"},{"key":"341_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2019.107006","volume":"248","author":"D Willsch","year":"2020","unstructured":"Willsch D, Willsch M, Raedt HD et al (2020) Support vector machines on the d-wave quantum annealer. Comput Phys Commun 248:107006. https:\/\/doi.org\/10.1016\/j.cpc.2019.107006","journal-title":"Comput Phys Commun"},{"issue":"13","key":"341_CR52","doi-asserted-by":"publisher","first-page":"3384","DOI":"10.1021\/acs.jpcb.7b10371","volume":"122","author":"R Xia","year":"2018","unstructured":"Xia R, Bian T, Kais S (2018) Electronic structure calculations and the ising hamiltonian. J Phys Chem B 122(13):3384\u20133395. https:\/\/doi.org\/10.1021\/acs.jpcb.7b10371","journal-title":"J Phys Chem B"}],"container-title":["Quantum Machine Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42484-026-00341-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42484-026-00341-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42484-026-00341-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T11:46:45Z","timestamp":1771501605000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42484-026-00341-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,19]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["341"],"URL":"https:\/\/doi.org\/10.1007\/s42484-026-00341-4","relation":{},"ISSN":["2524-4906","2524-4914"],"issn-type":[{"value":"2524-4906","type":"print"},{"value":"2524-4914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,19]]},"assertion":[{"value":"16 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 February 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":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"15"}}