{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:04:13Z","timestamp":1757617453606,"version":"3.44.0"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"7-8","license":[{"start":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T00:00:00Z","timestamp":1733529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T00:00:00Z","timestamp":1733529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"National College Students' Innovation and Entrepreneurship Training Plan Program","award":["202410289027Z"],"award-info":[{"award-number":["202410289027Z"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"crossref","award":["62176221","62076111"],"award-info":[{"award-number":["62176221","62076111"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Sichuan Science and Technology Program","award":["2024NSFTD0036"],"award-info":[{"award-number":["2024NSFTD0036"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1007\/s13042-024-02472-1","type":"journal-article","created":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T07:17:03Z","timestamp":1733555823000},"page":"4063-4076","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Star: semi-supervised tripartite attribute reduction"],"prefix":"10.1007","volume":"16","author":[{"given":"Keyu","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Damo","family":"Qian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianrui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xibei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tengyu","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,7]]},"reference":[{"key":"2472_CR1","volume":"222","author":"M Akram","year":"2023","unstructured":"Akram M, Nawaz HS, Deveci M (2023) Attribute reduction and information granulation in Pythagorean fuzzy formal contexts. IEEE Trans Fuzzy Syst 222:119794","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2472_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2024.109256","volume":"173","author":"NN Thuy","year":"2024","unstructured":"Thuy NN, Wongthanavasu S (2024) Attribute reduction with fuzzy divergence-based weighted neighborhood rough sets. Int J Approxim Reason 173:109256","journal-title":"Int J Approxim Reason"},{"key":"2472_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.121467","volume":"689","author":"C Zhang","year":"2025","unstructured":"Zhang C, Lu Z, Dai J (2025) Incremental attribute reduction for dynamic fuzzy decision information systems based on fuzzy knowledge granularity. Inf Sci 689:121467","journal-title":"Inf Sci"},{"key":"2472_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125323","volume":"260","author":"VKH Turaga","year":"2025","unstructured":"Turaga VKH, Chebrolu S (2025) Rapid and optimized parallel attribute reduction based on neighborhood rough sets and MapReduce. Expert Syst Appl 260:125323","journal-title":"Expert Syst Appl"},{"key":"2472_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.107102","volume":"100","author":"P Theerthagiri","year":"2025","unstructured":"Theerthagiri P (2025) Liver disease classification using histogram-based gradient boosting classification tree with feature selection algorithm. Biomed Signal Process Control 100:107102","journal-title":"Biomed Signal Process Control"},{"key":"2472_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2024.129997","volume":"651","author":"A Moslemi","year":"2024","unstructured":"Moslemi A, Bidar M (2024) Dual-dual subspace learning with low-rank consideration for feature selection. Physica A 651:129997","journal-title":"Physica A"},{"key":"2472_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128361","volume":"607","author":"H Chamlal","year":"2024","unstructured":"Chamlal H, Benzmane A, Ouaderhman T (2024) Maximal cliques-based hybrid high-dimensional feature selection with interaction screening for regression. Neurocomputing 607:128361","journal-title":"Neurocomputing"},{"key":"2472_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2024.103923","volume":"62","author":"A Moslemi","year":"2025","unstructured":"Moslemi A, Jamshidi M (2025) Unsupervised feature selection using sparse manifold learning: auto-encoder approach. Inf Process Manag 62:103923","journal-title":"Inf Process Manag"},{"key":"2472_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111069","volume":"158","author":"A Hassan","year":"2025","unstructured":"Hassan A, Paik JH, Khare SR, Hassan SA (2025) A wrapper feature selection approach using Markov blankets. Pattern Recognit 158:111069","journal-title":"Pattern Recognit"},{"key":"2472_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-024-02406-x","author":"D Qian","year":"2024","unstructured":"Qian D, Liu K, Wang J, Zhang S, Yang X (2024) Attribute reduction based on directional semi-neighborhood rough set. Int J Mach Learn Cybern. https:\/\/doi.org\/10.1007\/s13042-024-02406-x","journal-title":"Int J Mach Learn Cybern"},{"key":"2472_CR11","doi-asserted-by":"crossref","unstructured":"Miao J, Chen C, Liu F, Hao W, Heng PA (2023) Caussl: causality-inspired semi-supervised learning for medical image segmentation. In: 2023 IEEE\/CVF international conference on computer vision, pp 21369\u201321380","DOI":"10.1109\/ICCV51070.2023.01959"},{"issue":"5","key":"2472_CR12","doi-asserted-by":"publisher","first-page":"5244","DOI":"10.1109\/TKDE.2022.3145347","volume":"35","author":"Z Jiang","year":"2023","unstructured":"Jiang Z, Zhan Y, Mao Q, Du Y (2023) Semi-supervised clustering under a \u201ccompact-cluster\u2019\u2019 assumption. IEEE Trans Knowl Data Eng 35(5):5244\u20135256","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2472_CR13","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.neucom.2017.02.019","volume":"239","author":"Z Karimi","year":"2017","unstructured":"Karimi Z, Ghidary S (2017) Semi-supervised classification in stratified spaces by considering non-interior points using Laplacian behavior. Neurocomputing 239:223\u2013231","journal-title":"Neurocomputing"},{"issue":"5","key":"2472_CR14","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1109\/TNNLS.2012.2186825","volume":"23","author":"Y Wang","year":"2012","unstructured":"Wang Y, Chen S, Zhou Z-H (2012) New semi-supervised classification method based on modified cluster assumption. IEEE Trans Neural Netw Learn Syst 23(5):689\u2013702","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2472_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-01548-9","volume-title":"Introduction to semi-supervised learning","author":"X Zhu","year":"2009","unstructured":"Zhu X, Goldberg A (2009) Introduction to semi-supervised learning. Springer"},{"issue":"3","key":"2472_CR16","first-page":"2299","volume":"35","author":"D Shi","year":"2023","unstructured":"Shi D, Zhu L, Li J, Cheng Z, Liu Z (2023) Binary label learning for semi-supervised feature selection. IEEE Trans Knowl Data Eng 35(3):2299\u20132312","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"2472_CR17","doi-asserted-by":"publisher","first-page":"2899","DOI":"10.1109\/TKDE.2020.3014262","volume":"34","author":"K Benabdeslem","year":"2022","unstructured":"Benabdeslem K, Mansouri DEK, Makkhongkaew R (2022) sCOs: semi-supervised co-selection by a similarity preserving approach. IEEE Trans Knowl Data Eng 34(6):2899\u20132911","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"9","key":"2472_CR18","doi-asserted-by":"publisher","first-page":"2460","DOI":"10.1109\/TCYB.2016.2636339","volume":"47","author":"J Dai","year":"2017","unstructured":"Dai J, Hu Q, Zhang J, Hu H, Zheng N (2017) Attribute selection for partially labeled categorical data by rough set approach. IEEE Trans Cybern 47(9):2460\u20132471","journal-title":"IEEE Trans Cybern"},{"key":"2472_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119660","volume":"652","author":"Z Guo","year":"2024","unstructured":"Guo Z, Shen Y, Yang T, Li Y-J, Deng Y, Qian Y (2024) Semi-supervised feature selection based on fuzzy related family. Inf Sci 652:119660","journal-title":"Inf Sci"},{"key":"2472_CR20","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.knosys.2018.11.034","volume":"165","author":"K Liu","year":"2019","unstructured":"Liu K, Yang X, Yu H, Mi J, Wang P, Chen X (2019) Rough set based semi-supervised feature selection via ensemble selector. Knowl-Based Syst 165:282\u2013296","journal-title":"Knowl-Based Syst"},{"key":"2472_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119130","volume":"214","author":"F Karimi","year":"2023","unstructured":"Karimi F, Dowlatshahi MB, Amin H (2023) SemiACO: a semi-supervised feature selection based on ant colony optimization. Expert Syst Appl 214:119130","journal-title":"Expert Syst Appl"},{"key":"2472_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2024.102345","volume":"107","author":"C Zhang","year":"2024","unstructured":"Zhang C, Fan W, Wang B, Chen C, Li H (2024) Self-paced semi-supervised feature selection with application to multi-modal Alzheimer\u2019s disease classification. Inf Fusion 107:102345","journal-title":"Inf Fusion"},{"key":"2472_CR23","doi-asserted-by":"publisher","first-page":"7750","DOI":"10.1007\/s10489-024-05578-9","volume":"54","author":"D Qian","year":"2024","unstructured":"Qian D, Liu K, Zhang S, Yang X (2024) Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy. Appl Intell 54:7750\u20137764","journal-title":"Appl Intell"},{"key":"2472_CR24","doi-asserted-by":"publisher","first-page":"2792","DOI":"10.1109\/TASLP.2021.3097215","volume":"29","author":"H Azadi","year":"2021","unstructured":"Azadi H, Akbarzadeh-T M-R, Kobravi H-R, Shoeibi A (2021) Robust voice feature selection using interval type-2 fuzzy AHP for automated diagnosis of Parkinson\u2019s disease. IEEE\/ACM Trans Audio Speech Lang Process 29:2792\u20132802","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"issue":"8","key":"2472_CR25","doi-asserted-by":"publisher","first-page":"2886","DOI":"10.1109\/TFUZZ.2021.3096212","volume":"30","author":"J Chen","year":"2022","unstructured":"Chen J, Lin Y, Mi J, Li S, Ding W (2022) A spectral feature selection approach with kernelized fuzzy rough sets. IEEE Trans Fuzzy Syst 30(8):2886\u20132901","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"2","key":"2472_CR26","doi-asserted-by":"publisher","first-page":"874","DOI":"10.1109\/TCYB.2020.3015756","volume":"51","author":"Y Hu","year":"2021","unstructured":"Hu Y, Zhang Y, Gong D (2021) Multiobjective particle swarm optimization for feature selection with fuzzy cost. IEEE Trans Cybern 51(2):874\u2013888","journal-title":"IEEE Trans Cybern"},{"issue":"8","key":"2472_CR27","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1109\/TCYB.2014.2357892","volume":"45","author":"P Maji","year":"2015","unstructured":"Maji P, Garai P (2015) IT2 fuzzy-rough sets and max relevance-max significance criterion for attribute selection. IEEE Trans Cybern 45(8):1657\u20131668","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"2472_CR28","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1109\/TETCI.2020.3044679","volume":"6","author":"Q Lou","year":"2022","unstructured":"Lou Q, Deng Z, Choi K-S, Shen H, Wang J, Wang S (2022) Robust multi-label relief feature selection based on fuzzy margin co-optimization. IEEE Trans Emerg Top Comput Intell 6(2):387\u2013398","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"issue":"1","key":"2472_CR29","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1109\/TFUZZ.2022.3185285","volume":"31","author":"J Wan","year":"2023","unstructured":"Wan J, Chen H, Li T, Sang B, Yuan Z (2023) Feature grouping and selection with graph theory in robust fuzzy rough approximation space. IEEE Trans Fuzzy Syst 31(1):213\u2013225","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"12","key":"2472_CR30","doi-asserted-by":"publisher","first-page":"4516","DOI":"10.1109\/TFUZZ.2023.3287193","volume":"31","author":"T Yin","year":"2023","unstructured":"Yin T, Chen H, Yuan Z, Wan J, Liu K, Horng S-J, Li T (2023) A robust multilabel feature selection approach based on graph structure considering fuzzy dependency and feature interaction. IEEE Trans Fuzzy Syst 31(12):4516\u20134528","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"12","key":"2472_CR31","doi-asserted-by":"publisher","first-page":"3743","DOI":"10.1109\/TFUZZ.2020.3026834","volume":"29","author":"R Zhang","year":"2021","unstructured":"Zhang R, Li X (2021) Regularized regression with fuzzy membership embedding for unsupervised feature selection. IEEE Trans Fuzzy Syst 29(12):3743\u20133753","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2472_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124600","volume":"255","author":"Q Guo","year":"2024","unstructured":"Guo Q, Liu K, Xu T, Wang P, Yang X (2024) Fuzzy feature factorization machine: bridging feature interaction, selection, and construction. Expert Syst Appl 255:124600","journal-title":"Expert Syst Appl"},{"key":"2472_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107616","volume":"129","author":"Q Guo","year":"2024","unstructured":"Guo Q, Yang X, Zhang F, Xu T (2024) Perturbation-augmented graph convolutional networks: a graph contrastive learning architecture for effective node classification tasks. Eng Appl Artif Intell 129:107616","journal-title":"Eng Appl Artif Intell"},{"key":"2472_CR34","unstructured":"Chen H, Tao R, Fan Y, Wang Y, Wang J, Schiele B, Xie X, Raj B, Savvides M (2023) SoftMatch: addressing the quantity-quality tradeoff in semi-supervised learning. In: 2023 international conference on learning representations"},{"issue":"7","key":"2472_CR35","doi-asserted-by":"publisher","first-page":"2721","DOI":"10.1109\/TFUZZ.2021.3093202","volume":"30","author":"Z Huang","year":"2022","unstructured":"Huang Z, Li J, Qian Y (2022) Noise-tolerant fuzzy-$$\\beta $$-covering-based multigranulation rough sets and feature subset selection. IEEE Trans Fuzzy Syst 30(7):2721\u20132735","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"3","key":"2472_CR36","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1109\/TFUZZ.2018.2862870","volume":"27","author":"A Tan","year":"2019","unstructured":"Tan A, Wu W-Z, Qian Y, Liang J, Chen J, Li J (2019) Intuitionistic fuzzy rough set-based granular structures and attribute subset selection. IEEE Trans Fuzzy Syst 27(3):527\u2013539","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"4","key":"2472_CR37","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1109\/TFUZZ.2016.2574918","volume":"25","author":"C Wang","year":"2017","unstructured":"Wang C, Qi Y, Shao M, Hu Q, Chen D, Qian Y, Lin Y (2017) A fitting model for feature selection with fuzzy rough sets. IEEE Trans Fuzzy Syst 25(4):741\u2013753","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"1","key":"2472_CR38","first-page":"679","volume":"39","author":"X Rao","year":"2020","unstructured":"Rao X, Liu K, Song J, Yang X, Qian Y (2020) Gaussian kernel fuzzy rough based attribute reduction: an acceleration approach. J Intell Fuzzy Syst 39(1):679\u2013695","journal-title":"J Intell Fuzzy Syst"},{"issue":"11","key":"2472_CR39","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1109\/TKDE.2010.260","volume":"23","author":"Q Hu","year":"2011","unstructured":"Hu Q, Yu D, Pedrycz W, Chen D (2011) Kernelized fuzzy rough sets and their applications. IEEE Trans Knowl Data Eng 23(11):1649\u20131667","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"9","key":"2472_CR40","doi-asserted-by":"publisher","first-page":"3486","DOI":"10.1109\/TFUZZ.2021.3117449","volume":"30","author":"X Yang","year":"2022","unstructured":"Yang X, Li Y, Liu D, Li T (2022) Hierarchical fuzzy rough approximations with three-way multigranularity learning. IEEE Trans Fuzzy Syst 30(9):3486\u20133500","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"9","key":"2472_CR41","doi-asserted-by":"publisher","first-page":"3395","DOI":"10.1109\/TFUZZ.2021.3114734","volume":"30","author":"Z Yuan","year":"2022","unstructured":"Yuan Z, Chen H, Zhang P, Wan J, Li T (2022) A novel unsupervised approach to heterogeneous feature selection based on fuzzy mutual information. IEEE Trans Fuzzy Syst 30(9):3395\u20133409","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"3","key":"2472_CR42","doi-asserted-by":"publisher","first-page":"3514","DOI":"10.1109\/TNNLS.2022.3193929","volume":"35","author":"P Zhang","year":"2024","unstructured":"Zhang P, Li T, Yuan Z, Luo C, Liu K, Yang X (2024) Heterogeneous feature selection based on neighborhood combination entropy. IEEE Trans Neural Netw Learn Syst 35(3):3514\u20133527","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"9","key":"2472_CR43","doi-asserted-by":"publisher","first-page":"3248","DOI":"10.1109\/TFUZZ.2023.3250639","volume":"31","author":"Z Wang","year":"2023","unstructured":"Wang Z, Chen H, Yuan Z, Wan J, Li T (2023) Multiscale fuzzy entropy-based feature selection. IEEE Trans Fuzzy Syst 31(9):3248\u20133262","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2472_CR44","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1016\/j.ins.2022.07.102","volume":"609","author":"J Lai","year":"2022","unstructured":"Lai J, Chen H, Li T, Yang X (2022) Adaptive graph learning for semi-supervised feature selection with redundancy minimization. Inf Sci 609:465\u2013488","journal-title":"Inf Sci"},{"key":"2472_CR45","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/s41066-018-00151-5","volume":"5","author":"K Liu","year":"2020","unstructured":"Liu K, Tsang ECC, Song J, Yu H, Chen X, Yang X (2020) Neighborhood attribute reduction approach to partially labeled data. Granul Comput 5:239\u2013250","journal-title":"Granul Comput"},{"key":"2472_CR46","doi-asserted-by":"publisher","first-page":"1842","DOI":"10.1016\/j.neucom.2007.06.014","volume":"71","author":"J Zhao","year":"2008","unstructured":"Zhao J, Lu K, He X (2008) Locality sensitive semi-supervised feature selection. Neurocomputing 71:1842\u20131849","journal-title":"Neurocomputing"},{"issue":"9","key":"2472_CR47","doi-asserted-by":"publisher","first-page":"1974","DOI":"10.1109\/TNNLS.2016.2562670","volume":"28","author":"J Xu","year":"2017","unstructured":"Xu J, Tang B, He HB, Man H (2017) Semisupervised feature selection based on relevance and redundancy criteria. IEEE Trans Neural Netw Learn Syst 28(9):1974\u20131984","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"10","key":"2472_CR48","doi-asserted-by":"publisher","first-page":"3384","DOI":"10.1109\/TFUZZ.2023.3255893","volume":"31","author":"K Liu","year":"2023","unstructured":"Liu K, Li T, Yang X, Chen H, Wang J, Deng Z (2023) SemiFREE: semisupervised feature selection with fuzzy relevance and redundancy. IEEE Trans Fuzzy Syst 31(10):3384\u20133396","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2472_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106224","volume":"204","author":"QQ Pang","year":"2020","unstructured":"Pang QQ, Zhang L (2020) Semi-supervised neighborhood discrimination index for feature selection. Knowl-Based Syst 204:106224","journal-title":"Knowl-Based Syst"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02472-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-024-02472-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02472-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T05:05:28Z","timestamp":1757135128000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-024-02472-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,7]]},"references-count":49,"journal-issue":{"issue":"7-8","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["2472"],"URL":"https:\/\/doi.org\/10.1007\/s13042-024-02472-1","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2024,12,7]]},"assertion":[{"value":"30 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 December 2024","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 have no conflict of interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}