{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T02:39:22Z","timestamp":1772159962581,"version":"3.50.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"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":["Computing"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s00607-025-01574-0","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T13:28:42Z","timestamp":1764941322000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Blockchain-enabled hybrid evolutionary scheduling for cloud resource optimization"],"prefix":"10.1007","volume":"108","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-6591-2873","authenticated-orcid":false,"given":"Seyed","family":"Mahdi Hosseini","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5145-2013","authenticated-orcid":false,"given":"Ali","family":"Broumandnia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramin","family":"Karimi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"1574_CR1","volume":"37","author":"AM Yadav","year":"2023","unstructured":"Yadav AM, Sharma SC (2023) Cooperative task scheduling secured with blockchain in sustainable mobile edge computing. Sustain Comput Inform Syst 37:100843","journal-title":"Sustain Comput Inform Syst"},{"issue":"1","key":"1574_CR2","doi-asserted-by":"publisher","DOI":"10.1080\/23311916.2024.2328355","volume":"11","author":"VRSP Alla","year":"2024","unstructured":"Alla VRSP, Medikondu NR, Parige LS, Satyanarayana K, Kankhva VS, Dhaliwal N, Saxena AK (2024) Optimizing task scheduling in cloud computing: a hybrid artificial intelligence approach. Cogent Eng 11(1):2328355. https:\/\/doi.org\/10.1080\/23311916.2024.2328355","journal-title":"Cogent Eng"},{"key":"1574_CR3","doi-asserted-by":"crossref","unstructured":"Alhaidari F, Balharith T, Al-Yahyan E (2019). Comparative analysis for task scheduling algorithms on cloud computing. In: Proceedings of the 2019 International Conference on Computer and Information Sciences (ICCIS) pp. 1\u20136","DOI":"10.1109\/ICCISci.2019.8716470"},{"key":"1574_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/s12008-023-01488-1","author":"VRSP Alla","year":"2023","unstructured":"Alla VRSP, Medikondu NR, Kanakavalli PB, Ravulapalli VP (2023) Design and development of mixed integer programming model for scheduling tasks through artificial intelligence. International Journal on Interactive Design and Manufacturing (IJIDeM). https:\/\/doi.org\/10.1007\/s12008-023-01488-1","journal-title":"International Journal on Interactive Design and Manufacturing (IJIDeM)"},{"key":"1574_CR5","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.future.2018.09.014","volume":"91","author":"A Arunarani","year":"2019","unstructured":"Arunarani A, Manjula D, Sugumaran V (2019) Task scheduling techniques in cloud computing: a literature survey. Future Gener Comput Syst 91:407\u2013415. https:\/\/doi.org\/10.1016\/j.future.2018.09.014","journal-title":"Future Gener Comput Syst"},{"issue":"4","key":"1574_CR6","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.icte.2017.08.001","volume":"4","author":"N Dordaie","year":"2018","unstructured":"Dordaie N, Navimipour NJ (2018) Hybrid particle swarm optimization and hill climbing algorithm for task scheduling in cloud environments. ICT Express 4(4):199\u2013202. https:\/\/doi.org\/10.1016\/j.icte.2017.08.001","journal-title":"ICT Express"},{"issue":"19","key":"1574_CR7","doi-asserted-by":"publisher","first-page":"13075","DOI":"10.1007\/s00521-021-06002-w","volume":"33","author":"P Pirozmand","year":"2021","unstructured":"Pirozmand P, Hosseinabadi AAR, Farrokhzad M, Sadeghilalimi M, Mirkamali S, Slowik A (2021) Multi-objective hybrid genetic algorithm for task scheduling problem in cloud computing. Neural Comput Appl 33(19):13075\u201313088. https:\/\/doi.org\/10.1007\/s00521-021-06002-w","journal-title":"Neural Comput Appl"},{"issue":"4","key":"1574_CR8","doi-asserted-by":"publisher","first-page":"1835","DOI":"10.1007\/s11277-019-06360-8","volume":"107","author":"A Kumar","year":"2019","unstructured":"Kumar A, Venkatesan M (2019) Multi-objective task scheduling using hybrid genetic-ant colony optimization algorithm in the cloud environment. Wirel Pers Commun 107(4):1835\u20131848. https:\/\/doi.org\/10.1007\/s11277-019-06360-8","journal-title":"Wirel Pers Commun"},{"issue":"16","key":"1574_CR9","doi-asserted-by":"publisher","first-page":"12103","DOI":"10.1007\/s00521-019-04266-x","volume":"32","author":"M Kumar","year":"2020","unstructured":"Kumar M, Sharma SC (2020) PSO-based novel resource scheduling technique to improve QoS parameters in cloud computing. Neural Comput Appl 32(16):12103\u201312126. https:\/\/doi.org\/10.1007\/s00521-019-04266-x","journal-title":"Neural Comput Appl"},{"key":"1574_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.suscom.2021.100517","volume":"30","author":"M Hussain","year":"2021","unstructured":"Hussain M, Wei LF, Lakhan A, Wali S, Ali S, Hussain A (2021) Energy and performance-efficient task scheduling in heterogeneous virtualized cloud computing. Sustain Comput Inform Syst 30:100517. https:\/\/doi.org\/10.1016\/j.suscom.2021.100517","journal-title":"Sustain Comput Inform Syst"},{"key":"1574_CR11","first-page":"411","volume":"6","author":"L Lv","year":"2021","unstructured":"Lv L, Zhou XD, Kang P, Fu XF, Tian XM (2021) Multi-objective firefly algorithm with hierarchical learning. J Netw Intell 6:411\u2013427","journal-title":"J Netw Intell"},{"key":"1574_CR12","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1934784","author":"AM Manasrah","year":"2018","unstructured":"Manasrah AM, Ba Ali H (2018) Workflow scheduling using hybrid GA-PSO algorithm in cloud computing. Wirel Commun Mob Comput. https:\/\/doi.org\/10.1155\/2018\/1934784","journal-title":"Wirel Commun Mob Comput"},{"issue":"1","key":"1574_CR13","doi-asserted-by":"publisher","first-page":"68","DOI":"10.5815\/ijitcs.2018.01.08","volume":"10","author":"R Nagar","year":"2018","unstructured":"Nagar R, Gupta DK, Singh RM (2018) Time effective workflow scheduling using genetic algorithm in cloud computing. Int J Inf Technol Comput Sci 10(1):68\u201375. https:\/\/doi.org\/10.5815\/ijitcs.2018.01.08","journal-title":"Int J Inf Technol Comput Sci"},{"issue":"2","key":"1574_CR14","doi-asserted-by":"publisher","first-page":"1081","DOI":"10.11591\/ijeecs.v18.i2.pp1081-1088","volume":"18","author":"S Potluri","year":"2020","unstructured":"Potluri S, Rao KS (2020) Optimization model for QoS-based task scheduling in the cloud computing environment. Indonesian J Electr Eng Comput Sci. 18(2):1081\u20131088. https:\/\/doi.org\/10.11591\/ijeecs.v18.i2.pp1081-1088","journal-title":"Indonesian J Electr Eng Comput Sci."},{"issue":"10","key":"1574_CR15","doi-asserted-by":"publisher","first-page":"3975","DOI":"10.1007\/s12652-019-01631-5","volume":"11","author":"A Ragmani","year":"2020","unstructured":"Ragmani A, Elomri A, Abghour N, Moussaid K, Rida M (2020) FACO: a hybrid fuzzy ant colony optimization algorithm for virtual machine scheduling in high-performance cloud computing. J Ambient Intell Humaniz Comput 11(10):3975\u20133987. https:\/\/doi.org\/10.1007\/s12652-019-01631-5","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"1574_CR16","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.future.2018.10.046","volume":"93","author":"X Zhou","year":"2019","unstructured":"Zhou X, Zhang G, Sun J, Zhou J, Wei T, Hu S (2019) Minimizing cost and makespan for workflow scheduling in the cloud using fuzzy dominance sort-based HEFT. Future Gener Comput Syst 93:278\u2013289. https:\/\/doi.org\/10.1016\/j.future.2018.10.046","journal-title":"Future Gener Comput Syst"},{"issue":"2","key":"1574_CR17","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1080\/03772063.2018.1486740","volume":"66","author":"JAJ Sujana","year":"2020","unstructured":"Sujana JAJ, Revathi T, Rajanayagam SJ (2020) Fuzzy-based security-driven optimistic scheduling of scientific workflows in cloud computing. IETE J Res 66(2):224\u2013241. https:\/\/doi.org\/10.1080\/03772063.2018.1486740","journal-title":"IETE J Res"},{"issue":"2","key":"1574_CR18","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1080\/1206212X.2019.1709288","volume":"44","author":"A Rezaeipanah","year":"2022","unstructured":"Rezaeipanah A, Mojarad M, Fakhari A (2022) Provide a new approach to increase fault tolerance in cloud computing using fuzzy logic. Int J Comput Appl 44(2):139\u2013147. https:\/\/doi.org\/10.1080\/1206212X.2019.1709288","journal-title":"Int J Comput Appl"},{"issue":"1","key":"1574_CR19","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1016\/j.asej.2020.07.003","volume":"12","author":"S Velliangiri","year":"2021","unstructured":"Velliangiri S, Karthikeyan P, Arul Xavier V, Baswaraj D (2021) Hybrid electro search with genetic algorithm for task scheduling in cloud computing. Ain Shams Eng J 12(1):631\u2013639. https:\/\/doi.org\/10.1016\/j.asej.2020.07.003","journal-title":"Ain Shams Eng J"},{"key":"1574_CR20","doi-asserted-by":"publisher","unstructured":"Winster GS (2022). An efficient task scheduling and data security in heterogeneous cloud computing using hybrid meta-heuristic algorithm and blockchain-based key aggregate cryptosystem. ICPECTS. https:\/\/doi.org\/10.1109\/ICPECTS56089.2022.10047356","DOI":"10.1109\/ICPECTS56089.2022.10047356"},{"key":"1574_CR21","doi-asserted-by":"publisher","DOI":"10.3390\/info13020092","volume":"13","author":"W Li","year":"2022","unstructured":"Li W, Fan Q, Dang F, Jiang Y, Wang H, Li S, Zhang X (2022) Multi-objective optimization of a task-scheduling algorithm for a secure cloud. Information 13:92. https:\/\/doi.org\/10.3390\/info13020092","journal-title":"Information"},{"key":"1574_CR22","doi-asserted-by":"publisher","first-page":"121","DOI":"10.3233\/WEB-190406","volume":"17","author":"X Geng","year":"2019","unstructured":"Geng X, Yu L, Bao J, Fu G (2019) Task scheduling algorithm based on priority list and task duplication in a cloud computing environment. Web Intell 17:121\u2013129. https:\/\/doi.org\/10.3233\/WEB-190406","journal-title":"Web Intell"},{"key":"1574_CR23","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/1500646","volume":"2022","author":"Y Zhu","year":"2022","unstructured":"Zhu Y, Yan F, Pan JS, Yu L, Bai Y, Wang W, He C, Shi Z (2022) Multi-group based Phasmatodea population evolution algorithm with multi-strategy for IoT electric bus scheduling. Wirel Commun Mob Comput 2022:1500646","journal-title":"Wirel Commun Mob Comput"},{"issue":"4","key":"1574_CR24","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1504\/IJCAT.2019.101168","volume":"60","author":"M Hanini","year":"2019","unstructured":"Hanini M, Kafhali SE, Salah K (2019) Dynamic VM allocation and traffic control to manage QoS and energy consumption in the cloud computing environment. Int J Comput Appl Technol 60(4):307\u2013316. https:\/\/doi.org\/10.1504\/IJCAT.2019.101168","journal-title":"Int J Comput Appl Technol"},{"key":"1574_CR25","doi-asserted-by":"publisher","unstructured":"Pandey S, Wu L, Guru SM, Buyya R (2020). Particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments. AINA, pp. 400\u2013407, https:\/\/doi.org\/10.1109\/AINA.2010.31","DOI":"10.1109\/AINA.2010.31"},{"key":"1574_CR26","first-page":"41","volume":"4","author":"JS Pan","year":"2020","unstructured":"Pan JS, Dao TK, Pan TS, Nguyen TT, Chu SC (2020) Multi-group grasshopper optimisation algorithm for application in capacitated vehicle routing problem. Data Sci Pattern Recognit 4:41\u201356","journal-title":"Data Sci Pattern Recognit"},{"key":"1574_CR27","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.jpdc.2020.03.010","volume":"142","author":"AFS Devaraj","year":"2020","unstructured":"Devaraj AFS, Elhoseny M, Dhanasekaran S, Lydia EL, Shankar K (2020) Hybridization of firefly and improved multi-objective PSO algorithm for energy-efficient load balancing in cloud computing environments. J Parallel Distrib Comput 142:36\u201345. https:\/\/doi.org\/10.1016\/j.jpdc.2020.03.010","journal-title":"J Parallel Distrib Comput"},{"key":"1574_CR28","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.future.2020.03.041","volume":"108","author":"D Ding","year":"2020","unstructured":"Ding D, Fan X, Zhao Y, Kang K, Yin Q, Zeng J (2020) Q-learning-based dynamic task scheduling for energy-efficient cloud computing. Future Gener Comput Syst 108:361\u2013371. https:\/\/doi.org\/10.1016\/j.future.2020.03.041","journal-title":"Future Gener Comput Syst"},{"key":"1574_CR29","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1016\/j.jnca.2018.12.009","volume":"128","author":"M Adhikari","year":"2019","unstructured":"Adhikari M, Nandy S, Amgoth T (2019) Meta heuristic-based task deployment mechanism for load balancing in IaaS cloud. J Netw Comput Appl 128:64\u201377. https:\/\/doi.org\/10.1016\/j.jnca.2018.12.009","journal-title":"J Netw Comput Appl"},{"key":"1574_CR30","unstructured":"Narayanan D, Santhanam K, Kazhamiaka F, Phanishayee A, Zaharia M (2020). Heterogeneity-aware cluster scheduling policies for deep learning workloads. In: Proceedings of the 14th USENIX symposium on operating systems design and implementation (OSDI), pp. 481\u2013498."},{"key":"1574_CR31","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s10586-021-03186-y","volume":"24","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A (2021) A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments. Cluster Comput 24:205\u2013223. https:\/\/doi.org\/10.1007\/s10586-021-03186-y","journal-title":"Cluster Comput"},{"key":"1574_CR32","doi-asserted-by":"crossref","unstructured":"Han P, Du C, Chen J (2018). A DEA-based hybrid algorithm for bi-objective task scheduling in cloud computing. In: 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)","DOI":"10.1109\/CCIS.2018.8691163"},{"key":"1574_CR33","doi-asserted-by":"crossref","unstructured":"Fu M, Fei T, Zhang L, Li H (2021). Research on location optimization of low-carbon cold chain logistics distribution center by FWA-artificial fish swarm algorithm. CISCE, pp. 529\u2013533","DOI":"10.1109\/CISCE52179.2021.9446043"},{"key":"1574_CR34","doi-asserted-by":"crossref","unstructured":"Anushree B, Arul Xavier VM (2018). Comparative analysis of latest task scheduling techniques in cloud computing environment. In: Proceedings of the second international conference on computing methodologies and communication (ICCMC), pp. 608\u2013611","DOI":"10.1109\/ICCMC.2018.8487908"},{"key":"1574_CR35","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-021-00246-6","author":"PC Song","year":"2021","unstructured":"Song PC, Chu SC, Pan JS, Yang H (2021) Simplified Phasmatodea population evolution algorithm for optimization. Complex Intell Syst. https:\/\/doi.org\/10.1007\/s40747-021-00246-6","journal-title":"Complex Intell Syst"},{"key":"1574_CR36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17088","author":"SS Mondal","year":"2021","unstructured":"Mondal SS, Sheoran N, Mitra S (2021) Scheduling of time-varying workloads using reinforcement learning. Proceedings of the AAAI Conference on Artificial Intelligence. https:\/\/doi.org\/10.1609\/aaai.v35i10.17088","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"1574_CR37","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.ipl.2006.10.005","volume":"102","author":"M Jiang","year":"2007","unstructured":"Jiang M, Luo YP, Yang SY (2007) Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm. Inf Process Lett 102:8\u201316","journal-title":"Inf Process Lett"},{"key":"1574_CR38","doi-asserted-by":"publisher","first-page":"2483","DOI":"10.1007\/s10586-019-03051-2","volume":"23","author":"JQ Li","year":"2020","unstructured":"Li JQ, Han YQ (2020) A hybrid multi-objective artificial bee colony algorithm for flexible task scheduling problems in cloud computing system. Clust Comput 23:2483\u20132499. https:\/\/doi.org\/10.1007\/s10586-019-03051-2","journal-title":"Clust Comput"},{"key":"1574_CR39","doi-asserted-by":"crossref","unstructured":"Lingkang Z, Yuwei L, Xue J (2020). Detection of abnormal data flow at network boundary of renewable energy power system. In: 2020 IEEE 3rd international conference on automation, electronics and electrical engineering (AUTEEE), pp. 309\u2013312","DOI":"10.1109\/AUTEEE50969.2020.9315697"},{"key":"1574_CR40","doi-asserted-by":"crossref","unstructured":"Qi B, Xiong L, Wang L, Chen Z, Huang L (2019). A weights and improved adaptive artificial fish swarm algorithm for path planning. In: 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), pp. 1698\u20131702","DOI":"10.1109\/ITAIC.2019.8785467"},{"key":"1574_CR41","doi-asserted-by":"crossref","unstructured":"Casola V, De Benedictis A, Rak M, Villano U (2018). Towards automated penetration testing for cloud applications. In: 2018 IEEE 27th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp. 24\u201329","DOI":"10.1109\/WETICE.2018.00012"},{"key":"1574_CR42","doi-asserted-by":"crossref","unstructured":"Mao H, Schwarzkopf M, Venkatakrishnan SB, Meng Z, Alizadeh M (2019). Learning scheduling algorithms for data processing clusters. In: ACM SIGCOMM Conference, pp. 270\u2013288","DOI":"10.1145\/3341302.3342080"},{"key":"1574_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcan.2019.07.001","author":"F Farhadian","year":"2019","unstructured":"Farhadian F, Kashani MMR, Rezazadeh J, Farahbakhsh R, Sandrasegaran K (2019) An efficient IoT cloud energy consumption based on genetic algorithm. Digit Commun Netw. https:\/\/doi.org\/10.1016\/j.dcan.2019.07.001","journal-title":"Digit Commun Netw"},{"issue":"4","key":"1574_CR44","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1007\/BF02948918","volume":"18","author":"X He","year":"2003","unstructured":"He X, Sun X, Von Laszewski G (2003) QoS-guided min-min heuristic for grid task scheduling. J Comput Sci Technol 18(4):442\u2013451. https:\/\/doi.org\/10.1007\/BF02948918","journal-title":"J Comput Sci Technol"},{"key":"1574_CR45","doi-asserted-by":"crossref","unstructured":"Ding Z, Fan X, Zhao Y, Kang K, Yin Q, Zeng J (2020). The improved equilibrium optimization algorithm with tent map. In: 5th International Conference on Computer and Communication Systems (ICCCS), pp. 343\u2013346","DOI":"10.1109\/ICCCS49078.2020.9118477"},{"issue":"1","key":"1574_CR46","doi-asserted-by":"publisher","first-page":"31","DOI":"10.3233\/ICA-170555","volume":"25","author":"F Padillo","year":"2018","unstructured":"Padillo F, Luna JM, Herrera F, Ventura S (2018) Mining association rules on big data through mapreduce genetic programming. Integr Comput-Aided Eng 25(1):31\u201348. https:\/\/doi.org\/10.3233\/ICA-170555","journal-title":"Integr Comput-Aided Eng"},{"key":"1574_CR47","first-page":"1","volume":"12","author":"J Wu","year":"2021","unstructured":"Wu J, Xu M, Liu FF, Huang M, Ma L, Lu ZM (2021) Solar wireless sensor network routing algorithm based on multi-objective particle swarm optimization. J Inf Hiding Multimedia Signal Process 12:1\u201311","journal-title":"J Inf Hiding Multimedia Signal Process"},{"issue":"1","key":"1574_CR48","first-page":"67","volume":"1","author":"MPK Shelke","year":"2012","unstructured":"Shelke MPK, Sontakke MS, Gawande AD (2012) Intrusion detection system for cloud computing. Int J Sci Technol Res 1(1):67\u201371","journal-title":"Int J Sci Technol Res"},{"key":"1574_CR49","unstructured":"Liang JJ, Qu BY, Suganthan PN (2013). Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization. Computational Intelligence Laboratory, Zhengzhou University"},{"key":"1574_CR50","first-page":"2301","volume":"6","author":"Z Lingkang","year":"2018","unstructured":"Lingkang Z, Yuwei L, Xue J (2018) Phasmatodea-based resource scheduling in cloud. IEEE Access 6:2301\u20132311","journal-title":"IEEE Access"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-025-01574-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00607-025-01574-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-025-01574-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T05:19:01Z","timestamp":1769836741000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00607-025-01574-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,5]]},"references-count":50,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["1574"],"URL":"https:\/\/doi.org\/10.1007\/s00607-025-01574-0","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"value":"0010-485X","type":"print"},{"value":"1436-5057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,5]]},"assertion":[{"value":"28 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 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 competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"4"}}