{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T08:13:13Z","timestamp":1776327193093,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2020YFB1707802"],"award-info":[{"award-number":["2020YFB1707802"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["F2021201020"],"award-info":[{"award-number":["F2021201020"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12071131"],"award-info":[{"award-number":["12071131"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s13042-023-02024-z","type":"journal-article","created":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T08:02:45Z","timestamp":1701244965000},"page":"2209-2228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Self-adaptive interval dominance-based feature selection for monotonic classification of interval-valued attributes"],"prefix":"10.1007","volume":"15","author":[{"given":"Jiankai","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongyan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junhai","family":"Zhai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,29]]},"reference":[{"key":"2024_CR1","doi-asserted-by":"crossref","unstructured":"Ben-David A, Sterling L, Pao YH (1989) Learning and classification of monotonic ordinal concepts. vol 5, Blackwell Publishing Ltd, pp 45\u201349","DOI":"10.1111\/j.1467-8640.1989.tb00314.x"},{"issue":"6","key":"2024_CR2","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1111\/j.1540-5915.1992.tb00453.x","volume":"23","author":"A Ben-David","year":"2010","unstructured":"Ben-David A (2010) Automatic generation of symbolic multiattribute ordinal knowledge-based DSSs: methodology and applications. Decis Sci 23(6):1357\u20131372","journal-title":"Decis Sci"},{"key":"2024_CR3","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.engappai.2017.02.006","volume":"60","author":"J Cano","year":"2017","unstructured":"Cano J, Aljohani NR, Abbasi RA, Alowidbi J, Garcia S (2017) Prototype selection to improve monotonic nearest neighbor. Eng Appl Artif Intell 60:128\u2013135","journal-title":"Eng Appl Artif Intell"},{"issue":"4","key":"2024_CR4","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/S0957-4174(03)00102-7","volume":"25","author":"MJ Kim","year":"2003","unstructured":"Kim MJ, Han I (2003) The discovery of experts\u2019 decision rules from qualitative bankruptcy data using genetic algorithms. Expert Syst Appl 25(4):637\u2013646","journal-title":"Expert Syst Appl"},{"issue":"16","key":"2024_CR5","doi-asserted-by":"crossref","first-page":"7235","DOI":"10.1016\/j.eswa.2014.05.035","volume":"41","author":"CC Chen","year":"2014","unstructured":"Chen CC, Li ST (2014) Credit rating with a monotonicity-constrained support vector machine model. Expert Syst Appl 41(16):7235\u20137247","journal-title":"Expert Syst Appl"},{"issue":"11","key":"2024_CR6","doi-asserted-by":"crossref","first-page":"2052","DOI":"10.1109\/TKDE.2011.149","volume":"24","author":"QH Hu","year":"2012","unstructured":"Hu QH, Che JX, Zhang L, Zhang D, Guo MZ, Yu DR (2012) Rank entropy based decision trees for monotonic classification. IEEE Trans Knowl Data Eng 24(11):2052\u20132064","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2024_CR7","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.knosys.2016.08.023","volume":"112","author":"SL Pei","year":"2016","unstructured":"Pei SL, Hu QH, Chen C (2016) Multivariate decision trees with monotonicity constraints. Knowl Based Syst 112:14\u201325","journal-title":"Knowl Based Syst"},{"key":"2024_CR8","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.ins.2017.10.006","volume":"424","author":"SL Pei","year":"2018","unstructured":"Pei SL, Hu QH (2018) Partially monotonic decision trees. Inf Sci 424:104\u2013117","journal-title":"Inf Sci"},{"issue":"1","key":"2024_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s43674-021-00007-7","volume":"2","author":"JK Chen","year":"2022","unstructured":"Chen JK, Li ZY, Wang X, Zhai JH (2022) A hybrid monotone decision tree model for interval-valued attributes. Adv Comput Intell 2(1):1\u201311","journal-title":"Adv Comput Intell"},{"issue":"9","key":"2024_CR10","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1109\/34.232084","volume":"15","author":"NP Archer","year":"2002","unstructured":"Archer NP, Wang S (2002) Learning bias in neural networks and an approach to controlling its effect in monotonic classification. IEEE Trans Pattern Anal Mach Intell 15(9):962\u2013966","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"2024_CR11","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1109\/TNN.2010.2044803","volume":"21","author":"H Daniels","year":"2010","unstructured":"Daniels H, Velikova M (2010) Monotone and partially monotone neural networks. IEEE Trans Neural Netw 21(6):906\u2013917","journal-title":"IEEE Trans Neural Netw"},{"key":"2024_CR12","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.neucom.2016.11.021","volume":"225","author":"H Zhu","year":"2016","unstructured":"Zhu H, Tsang E, Wang ZX, Ashfaq RAR (2016) Monotonic classification extreme learning machine. Neurocomputing 225:205\u2013213","journal-title":"Neurocomputing"},{"key":"2024_CR13","doi-asserted-by":"crossref","unstructured":"Duivesteijn W, Feelders A (2008) Nearest neighbour classification with monotonicity constraints. In: Joint European Conference on machine learning and knowledge discovery in databases, pp 301\u2013316","DOI":"10.1007\/978-3-540-87479-9_38"},{"key":"2024_CR14","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.neucom.2019.12.152","volume":"439","author":"S Gonzalez","year":"2021","unstructured":"Gonzalez S, Garcia S, Li S, John R, Herrera F (2021) Fuzzy k-Nearest Neighbors with monotonicity constraints: moving towards the robustness of monotonic noise. Neurocomputing 439:106\u2013121","journal-title":"Neurocomputing"},{"issue":"9","key":"2024_CR15","doi-asserted-by":"crossref","first-page":"3501","DOI":"10.1109\/TFUZZ.2021.3117450","volume":"30","author":"H Zhu","year":"2022","unstructured":"Zhu H, Wang XZ, Wang R (2022) Fuzzy monotonic K-nearest neighbor versus monotonic fuzzy K-Nearest neighbor. IEEE Trans Fuzzy Syst 30(9):3501\u20133513","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"5","key":"2024_CR16","doi-asserted-by":"crossref","first-page":"1713","DOI":"10.1109\/TFUZZ.2014.2374214","volume":"23","author":"ST Li","year":"2015","unstructured":"Li ST, Chen CC (2015) A regularized monotonic fuzzy support vector machine model for data mining with prior knowledge. IEEE Trans Fuzzy Syst 23(5):1713\u20131727","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2024_CR17","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.fss.2020.01.006","volume":"401","author":"Q Brabant","year":"2020","unstructured":"Brabant Q, Couceiro M, Dubois D, Henri P, Rico A (2020) Learning rule sets and Sugeno integrals for monotonic classification problems. Fuzzy Sets Syst 401:4\u201337","journal-title":"Fuzzy Sets Syst"},{"key":"2024_CR18","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.ins.2021.09.015","volume":"582","author":"ZH Deng","year":"2022","unstructured":"Deng ZH, Cao Y, Lou QD, Choi K, Wang ST (2022) Monotonic relation-constrained Takagi\u2013Sugeno\u2013Kang fuzzy system. Inf Sci 582:243\u2013257","journal-title":"Inf Sci"},{"issue":"10","key":"2024_CR19","doi-asserted-by":"crossref","first-page":"2717","DOI":"10.1109\/TKDE.2015.2429133","volume":"27","author":"YH Qian","year":"2015","unstructured":"Qian YH, Xu H, Liang JY, Liu B, Wang JT (2015) Fusing monotonic decision trees. IEEE Trans Knowl Data Eng 27(10):2717\u20132728","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"10","key":"2024_CR20","doi-asserted-by":"crossref","first-page":"2223","DOI":"10.1109\/TKDE.2017.2725832","volume":"29","author":"H Xu","year":"2017","unstructured":"Xu H, Wang W, Qian YH (2017) Fusing complete monotonic decision trees. IEEE Trans Knowl Data Eng 29(10):2223\u20132235","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"5","key":"2024_CR21","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1109\/TFUZZ.2019.2953024","volume":"28","author":"JT Wang","year":"2020","unstructured":"Wang JT, Qian YH, Li FJ, Ding WP (2020) Fusing fuzzy monotonic decision trees. IEEE Trans Fuzzy Syst 28(5):887\u2013900","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2024_CR22","doi-asserted-by":"crossref","first-page":"17002","DOI":"10.1109\/ACCESS.2020.2967780","volume":"8","author":"XB Qi","year":"2020","unstructured":"Qi XB, Guo HS, Artem Z, Wang WJ (2020) An interval-valued data classification method based on the unified representation frame. IEEE Access 8:17002\u201317012","journal-title":"IEEE Access"},{"key":"2024_CR23","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.neucom.2015.11.084","volume":"182","author":"FD Carvalho","year":"2016","unstructured":"Carvalho FD, Bertrand P, Simoes EC (2016) Batch SOM algorithms for interval-valued data with automatic weighting of the variables. Neurocomputing 182:66\u201381","journal-title":"Neurocomputing"},{"issue":"10","key":"2024_CR24","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1016\/j.patrec.2004.03.016","volume":"25","author":"D Guru","year":"2004","unstructured":"Guru D, Kiranagi B, Nagabhushan P (2004) Multivalued type proximity measure and concept of mutual similarity value useful for clustering symbolic patterns. Pattern Recogn Lett 25(10):1203\u20131213","journal-title":"Pattern Recogn Lett"},{"issue":"8","key":"2024_CR25","doi-asserted-by":"crossref","first-page":"1994","DOI":"10.1016\/j.camwa.2008.04.021","volume":"56","author":"YH Qian","year":"2008","unstructured":"Qian YH, Liang JY, Dang CY (2008) Interval ordered information systems. Comput Math Appl 56(8):1994\u20132009","journal-title":"Comput Math Appl"},{"issue":"1","key":"2024_CR26","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/S0377-2217(98)00127-1","volume":"117","author":"S Greco","year":"1999","unstructured":"Greco S, Matarazzo B, Slowinski R (1999) Rough approximation of a preference relation by dominance relations. Eur J Oper Res 117(1):63\u201383","journal-title":"Eur J Oper Res"},{"key":"2024_CR27","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/j.ins.2014.02.138","volume":"277","author":"M Szelag","year":"2014","unstructured":"Szelag M, Greco S, Slowi\u2019nski R (2014) Variable consistency dominance-based rough set approach to preference learning in multi-criteria ranking. Inf Sci 277:525\u2013552","journal-title":"Inf Sci"},{"key":"2024_CR28","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.ins.2016.09.012","volume":"373","author":"HM Chen","year":"2016","unstructured":"Chen HM, Li TR, Cai Y, Luo C, Fujita H (2016) Parallel attribute reduction in dominance-based neighborhood rough set. Inf Sci 373:351\u2013368","journal-title":"Inf Sci"},{"key":"2024_CR29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ijar.2020.05.002","volume":"124","author":"WT Li","year":"2020","unstructured":"Li WT, Xue XP, Xu WH, Zhan T, Fan BJ (2020) Double-quantitative variable consistency dominance-based rough set approach. Int J Approx Reason 124:1\u201326","journal-title":"Int J Approx Reason"},{"issue":"3","key":"2024_CR30","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1109\/TFUZZ.2019.2955883","volume":"29","author":"SY Yang","year":"2021","unstructured":"Yang SY, Zhang HY, Baets BD, Jah M, Shi G (2021) Quantitative dominance-based neighborhood rough sets via fuzzy preference relations. IEEE Trans Fuzzy Syst 29(3):515\u2013529","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"10","key":"2024_CR31","doi-asserted-by":"crossref","first-page":"2003","DOI":"10.1016\/j.ins.2010.01.015","volume":"180","author":"QH Hu","year":"2010","unstructured":"Hu QH, Yu DR, Guo MZ (2010) Fuzzy preference based rough sets. Inf Sci 180(10):2003\u20132022","journal-title":"Inf Sci"},{"key":"2024_CR32","volume":"10","author":"BB Sang","year":"2021","unstructured":"Sang BB, Chen HM, Yang L, Li TR, Xu WH, Luo C (2021) Feature selection for dynamic interval-valued ordered data based on fuzzy dominance neighborhood rough set. Knowl Based Syst 10:107223","journal-title":"Knowl Based Syst"},{"issue":"6","key":"2024_CR33","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1142\/S0218488519500417","volume":"27","author":"WH Shu","year":"2019","unstructured":"Shu WH, Qian WB, Xie YH, Tang ZP (2019) An efficient un-certainty measure-based attribute reduction approach for interval-valued data with missing values. Int J Uncertain Fuzz Knowl Based Syst 27(6):931\u2013947","journal-title":"Int J Uncertain Fuzz Knowl Based Syst"},{"key":"2024_CR34","first-page":"1188","volume":"06","author":"QH Hu","year":"2010","unstructured":"Hu QH, Guo MZ, Yu DR, Liu JF (2010) Information entropy for ordinal classification. Sci China Inf Sci 06:1188\u20131200","journal-title":"Sci China Inf Sci"},{"issue":"1","key":"2024_CR35","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1109\/TFUZZ.2011.2167235","volume":"20","author":"QH Hu","year":"2012","unstructured":"Hu QH, Pan WW, Zhang L, Zhang D, Song YP, Guo MZ, Yu DR (2012) Feature selection for monotonic classification. IEEE Trans Fuzzy Syst 20(1):69\u201381","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2024_CR36","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.knosys.2012.01.011","volume":"31","author":"QH Hu","year":"2012","unstructured":"Hu QH, Pan WW, Song YP, Yu DR (2012) Large-margin feature selection for monotonic classification. Knowl Based Syst 31:8\u201318","journal-title":"Knowl Based Syst"},{"key":"2024_CR37","volume":"240","author":"C Luo","year":"2022","unstructured":"Luo C, Pi H, Li TR, Chen HM, Huang YY (2022) Novel fuzzy rank discrimination measures for monotonic ordinal feature selection. Knowl Based Syst 240:108178","journal-title":"Knowl Based Syst"},{"issue":"12","key":"2024_CR38","doi-asserted-by":"crossref","first-page":"5181","DOI":"10.1109\/TFUZZ.2022.3169625","volume":"30","author":"BB Sang","year":"2022","unstructured":"Sang BB, Chen HM, Yang L, Wan JH, Li TR, Xu WH (2022) Feature selection considering multiple correlations based on soft fuzzy dominance rough sets for monotonic classification. IEEE Trans Fuzzy Syst 30(12):5181\u20135195","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2024_CR39","volume":"253","author":"BB Sang","year":"2022","unstructured":"Sang BB, Chen HM, Wan JH, Yang L, Li TR, Xu WH, Luo C (2022) Self-adaptive weighted interaction feature selection based on robust fuzzy dominance rough sets for monotonic classification. Knowl Based Syst 253:109523","journal-title":"Knowl Based Syst"},{"issue":"6","key":"2024_CR40","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1109\/TFUZZ.2021.3064686","volume":"30","author":"BB Sang","year":"2022","unstructured":"Sang BB, Chen HM, Yang L, Li TR, Xu WH (2022) Incremental feature selection using a conditional entropy based on fuzzy dominance neighborhood rough sets. IEEE Trans Fuzzy Syst 30(6):1683\u20131697","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"7","key":"2024_CR41","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1016\/j.knosys.2011.04.012","volume":"24","author":"B Huang","year":"2011","unstructured":"Huang B (2011) Graded dominance interval-based fuzzy objective information systems. Knowl Based Syst 24(7):1004\u20131012","journal-title":"Knowl Based Syst"},{"issue":"2","key":"2024_CR42","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1111\/exsy.12022","volume":"31","author":"B Sun","year":"2014","unstructured":"Sun B, Ma W, Gong Z (2014) Dominance-based rough set theory over interval-valued information systems. Expert Syst 31(2):185\u2013197","journal-title":"Expert Syst"},{"issue":"7","key":"2024_CR43","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1016\/j.ins.2008.11.020","volume":"179","author":"YY Yao","year":"2009","unstructured":"Yao YY, Zhao Y (2009) Discernibility matrix simplification for constructing attribute reducts. Inf Sci 179(7):867\u2013882","journal-title":"Inf Sci"},{"key":"2024_CR44","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.ins.2018.08.047","volume":"470","author":"N Xie","year":"2019","unstructured":"Xie N, Liu M, Li Z, Zhang G (2019) New measures of uncertainty for an interval-valued information system. Inf Sci 470:156\u2013174","journal-title":"Inf Sci"},{"key":"2024_CR45","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.ins.2013.06.047","volume":"251","author":"J Dai","year":"2013","unstructured":"Dai J, Wang W, Mi JS (2013) Uncertainty measurement for interval-valued information systems. Inf Sci 251:63\u201378","journal-title":"Inf Sci"},{"key":"2024_CR46","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3184120","author":"W Li","year":"2022","unstructured":"Li W, Zhou H, Xu W, Wang XZ, Pedrycz W (2022) Interval dominance-based feature selection for interval-valued ordered data. IEEE Trans Neural Netw Learn Syst. https:\/\/doi.org\/10.1109\/TNNLS.2022.3184120","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"3","key":"2024_CR47","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/S0165-0114(96)00262-X","volume":"94","author":"Y Nakahara","year":"1998","unstructured":"Nakahara Y (1998) User oriented ranking criteria and its application to fuzzy mathematical programming problems. Fuzzy Sets Syst 94(3):275\u2013286","journal-title":"Fuzzy Sets Syst"},{"key":"2024_CR48","doi-asserted-by":"crossref","unstructured":"Borowik G, Luba T, Zydek D (2011) Reduction of knowledge representation using logic minimization techniques. In: Proceedings of the 2011 International Conference on Systems Engineering, pp 482-485","DOI":"10.1109\/ICSEng.2011.98"},{"key":"2024_CR49","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.neunet.2016.04.005","volume":"80","author":"LV Utkin","year":"2016","unstructured":"Utkin LV, Chekh AI, Zhuk YA (2016) Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels. Neural Netw 80:53\u201366","journal-title":"Neural Netw"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-02024-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-023-02024-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-02024-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,23]],"date-time":"2024-05-23T05:27:10Z","timestamp":1716442030000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-023-02024-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,29]]},"references-count":49,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["2024"],"URL":"https:\/\/doi.org\/10.1007\/s13042-023-02024-z","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,29]]},"assertion":[{"value":"12 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 November 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}