{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T17:34:19Z","timestamp":1787592859082,"version":"build-2736575974"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T00:00:00Z","timestamp":1774051200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T00:00:00Z","timestamp":1774051200000},"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":["Netw Model Anal Health Inform Bioinforma"],"DOI":"10.1007\/s13721-026-00781-9","type":"journal-article","created":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T01:44:49Z","timestamp":1774057489000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Re-imagining spatio-temporal model for volumetric 3D brain tumor MRI image classification by spatio-spatial ResNet(2+1)D model"],"prefix":"10.1007","volume":"15","author":[{"given":"J.","family":"Vijaya","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harshvardhan","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shantanu","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Avani","family":"Gajallewar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,21]]},"reference":[{"issue":"9","key":"781_CR1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11091589","volume":"11","author":"I Abd El Kader","year":"2021","unstructured":"Abd El Kader I, Xu G, Shuai Z, Saminu S, Javaid I, Ahmad IS, Kamhi S (2021) Brain tumor detection and classification on MR images by a deep wavelet auto-encoder model. Diagnostics 11(9):1589","journal-title":"Diagnostics"},{"issue":"1","key":"781_CR2","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s40708-025-00279-6","volume":"12","author":"K Afnaan","year":"2025","unstructured":"Afnaan K, Arunbalaji CG, Singh T, Kumar R, Naik GR (2025) Boosting brain tumor detection with an optimized ResNet and explainability via Grad-CAM and LIME. Brain Informatics 12(1):33","journal-title":"Brain Informatics"},{"key":"781_CR3","doi-asserted-by":"crossref","unstructured":"Agalya D, Kamalakkannan S (2024) Detecting Brain Tumor Stages Using Convolutional AutoEncoder (CAE) with Hybrid Deep Learning Method. In 2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS) (pp. 796-803). IEEE","DOI":"10.1109\/ICSCSS60660.2024.10625600"},{"key":"781_CR4","doi-asserted-by":"crossref","unstructured":"Agrawal A, Maan V (2024) Brain tumor classification of mri scans using deep learning techniques. In 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) (pp. 1128-1133). IEEE","DOI":"10.1109\/IC3SE62002.2024.10593086"},{"issue":"5","key":"781_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics15050624","volume":"15","author":"RR Ali","year":"2025","unstructured":"Ali RR, Yaacob NM, Alqaryouti MH, Sadeq AE, Doheir M, Iqtait M, Yaacob SS (2025) Learning architecture for brain tumor classification based on deep convolutional neural network: classic and ResNet50. Diagnostics 15(5):624","journal-title":"Diagnostics"},{"key":"781_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.prime.2024.100723","volume":"9","author":"S Amarneni","year":"2024","unstructured":"Amarneni S, Valarmathi RS (2024) Diagnosing the MRI brain tumour images through RNN-LSTM. e-Prime-Advances in Electrical Engineering, Electronics and Energy 9:100723","journal-title":"e-Prime-Advances in Electrical Engineering, Electronics and Energy"},{"key":"781_CR7","doi-asserted-by":"crossref","unstructured":"Arora S, Sharma M (2021) Deep learning for brain tumor classification from mri images. In 2021 Sixth International Conference on Image Information Processing (ICIIP) (Vol. 6, pp. 409-412). IEEE","DOI":"10.1109\/ICIIP53038.2021.9702609"},{"key":"781_CR8","doi-asserted-by":"publisher","first-page":"2233","DOI":"10.1016\/j.matpr.2021.11.368","volume":"51","author":"N Bhagat","year":"2022","unstructured":"Bhagat N, Kaur G (2022) MRI brain tumor image classification with support vector machine. Mater Today Proc 51:2233\u20132244","journal-title":"Mater Today Proc"},{"issue":"1","key":"781_CR9","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-05572-6","volume":"12","author":"S Chatterjee","year":"2022","unstructured":"Chatterjee S, Nizamani FA, N\u00fcrnberger A, Speck O (2022) Classification of brain tumours in MR images using deep spatio-spatial models. Sci Rep 12(1):1505","journal-title":"Sci Rep"},{"issue":"15","key":"781_CR10","doi-asserted-by":"publisher","first-page":"45799","DOI":"10.1007\/s11042-023-17215-7","volume":"83","author":"S Das","year":"2024","unstructured":"Das S, Goswami RS (2024) Review, limitations, and future prospects of neural network approaches for brain tumor classification. Multimedia Tools Appl 83(15):45799\u201345841","journal-title":"Multimedia Tools Appl"},{"key":"781_CR11","doi-asserted-by":"crossref","unstructured":"Dipu NM, Shohan SA, Salam KMA (2021) Deep learning based brain tumor detection and classification. In 2021 International conference on intelligent technologies (CONIT) (pp. 1-6). IEEE","DOI":"10.1109\/CONIT51480.2021.9498384"},{"issue":"1","key":"781_CR12","doi-asserted-by":"publisher","first-page":"115","DOI":"10.21512\/commit.v19i1.12467","volume":"19","author":"IGSM Diyasa","year":"2025","unstructured":"Diyasa IGSM, Sunarko VI, Puspaningrum EY, Asy\u2019ari V, Ibrahim MZ (2025) Optimization of multi-section and partially augmented magnetic resonance imaging (MRI) images for brain tumor classification using ResNet-50. CommIT (Communication and Information Technology) Journal 19(1):115\u2013128","journal-title":"CommIT (Communication and Information Technology) Journal"},{"issue":"5","key":"781_CR13","first-page":"1489","volume":"106","author":"N Evuri","year":"2025","unstructured":"Evuri N, Pakala SR, Samantula S, Chebrolu S (2025) 3d swin-res-segnet: a hybrid transformer and cnn model for brain tumor segmentation using MRI scans. Journal of The Institution of Engineers (India): Series B 106(5):1489\u20131499","journal-title":"Journal of The Institution of Engineers (India): Series B"},{"issue":"3","key":"781_CR14","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13030561","volume":"13","author":"E Ghafourian","year":"2023","unstructured":"Ghafourian E, Samadifam F, Fadavian H, Jerfi Canatalay P, Tajally A, Channumsin S (2023) An ensemble model for the diagnosis of brain tumors through MRIs. Diagnostics (Basel) 13(3):561","journal-title":"Diagnostics (Basel)"},{"key":"781_CR15","doi-asserted-by":"crossref","unstructured":"Hafeez MA, Kayasandik CB, Dogan MY (2022) Brain tumor classification using MRI images and convolutional neural networks. In 2022 30th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE","DOI":"10.1109\/SIU55565.2022.9864962"},{"key":"781_CR16","doi-asserted-by":"crossref","unstructured":"Han SH, Han Y, Park K, Lee S, Lee W (2025). SpatIO: Spatial Physical Computing Toolkit Based on Extended Reality. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1-22)","DOI":"10.1145\/3706598.3713747"},{"issue":"7","key":"781_CR17","doi-asserted-by":"publisher","first-page":"3087","DOI":"10.1109\/TCSVT.2022.3232889","volume":"33","author":"X Huang","year":"2022","unstructured":"Huang X, Li X, Ye Y, Feng S, Luo C, Zhang B (2022) On understanding of spatio-temporal prediction model. IEEE Trans Circuits Syst Video Technol 33(7):3087\u20133103","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"781_CR18","doi-asserted-by":"crossref","unstructured":"Hussain A, Khunteta A (2020) Semantic segmentation of brain tumor from MRI images and SVM classification using GLCM features. In 2020 second international conference on inventive research in computing applications (ICIRCA) (pp. 38-43). IEEE","DOI":"10.1109\/ICIRCA48905.2020.9183385"},{"key":"781_CR19","first-page":"118","volume-title":"International MICCAI Brainlesion Workshop","author":"F Isensee","year":"2020","unstructured":"Isensee F, J\u00e4ger PF, Full PM, Vollmuth P, Maier-Hein KH (2020) nnU-Net for brain tumor segmentation. International MICCAI Brainlesion Workshop. Springer International Publishing, Cham, pp 118\u2013132"},{"key":"781_CR20","first-page":"28","volume-title":"EfficientNet and mixed convolution network for three-class brain tumor magnetic resonance image classification","author":"BV Isunuri","year":"2024","unstructured":"Isunuri BV, Kakarla J (2024) EfficientNet and mixed convolution network for three-class brain tumor magnetic resonance image classification. Soft Computing-A Fusion of Foundations, Methodologies & Applications, p 28"},{"issue":"3","key":"781_CR21","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1504\/IJMME.2024.140697","volume":"15","author":"B Jin","year":"2024","unstructured":"Jin B, Xu X (2024a) Regional steel price index predictions for North China through machine learning. Int J Min Miner Eng 15(3):314\u2013350","journal-title":"Int J Min Miner Eng"},{"issue":"04","key":"781_CR22","doi-asserted-by":"publisher","first-page":"2450023","DOI":"10.1142\/S1752890924500235","volume":"17","author":"B Jin","year":"2024","unstructured":"Jin B, Xu X (2024b) Machine learning coffee price predictions. J Uncertain Syst 17(04):2450023","journal-title":"J Uncertain Syst"},{"key":"781_CR23","volume-title":"Forecasts of coking coal futures price indices through Gaussian process regressions","author":"B Jin","year":"2024","unstructured":"Jin B, Xu X (2024c) Forecasts of coking coal futures price indices through Gaussian process regressions. Miner, Econ"},{"key":"781_CR24","doi-asserted-by":"crossref","unstructured":"Jin B, Xu X (2024d) Machine learning price index forecasts of flat steel products. Mineral Econ","DOI":"10.1007\/s13563-024-00457-8"},{"key":"781_CR25","doi-asserted-by":"publisher","DOI":"10.1142\/s2424786325500033","author":"B Jin","year":"2025","unstructured":"Jin B, Xu X (2025a) China commodity price index (CCPI) forecasting via the neural network. Int J Fin Eng. https:\/\/doi.org\/10.1142\/s2424786325500033","journal-title":"Int J Fin Eng"},{"key":"781_CR26","doi-asserted-by":"crossref","unstructured":"Jin B, Xu X (2025b) High-frequency CSI300 spot and futures price predictions via the neural network. Journal of Uncertain Systems, 2550008","DOI":"10.1142\/S1752890925500084"},{"key":"781_CR27","doi-asserted-by":"crossref","unstructured":"Jin B, Xu X (2025c) Contemporaneous causal orderings among prices of retail properties: evidence from Chinese cities through vector error-correction modeling and directed acyclic graphs. Journal of Financial Management of Property and Construction, (ahead-of-print)","DOI":"10.1108\/JFMPC-03-2024-0019"},{"key":"781_CR28","doi-asserted-by":"crossref","unstructured":"Jin B, Xu X (2025d) A study of contemporaneous residential real estate price causation across major Jiangsu province cities: Methodology using vector error-correction models and directed acyclic graphs. Economics Open, 2550008","DOI":"10.1142\/S308284142550008X"},{"key":"781_CR29","doi-asserted-by":"crossref","unstructured":"Jin B, Xu X, Zhang Y (2025e) Peanut oil price change forecasts through the neural network. foresight, 27(3), 595-612","DOI":"10.1108\/FS-01-2023-0016"},{"issue":"1","key":"781_CR30","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-19689-x","volume":"15","author":"S Khan","year":"2025","unstructured":"Khan S, Dilshad N, Ahmad N, Noor S, AlQahtani SA (2025) Integrating AI in security information and event management for real time cyber defense. Sci Rep 15(1):35872","journal-title":"Sci Rep"},{"issue":"1","key":"781_CR31","doi-asserted-by":"publisher","DOI":"10.1186\/s13040-024-00415-8","volume":"18","author":"S Khan","year":"2025","unstructured":"Khan S, Noor S, Javed T, Naseem A, Aslam F, AlQahtani SA, Ahmad N (2025) XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites. BioData Min 18(1):12","journal-title":"BioData Min"},{"issue":"1","key":"781_CR32","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-024-05917-0","volume":"25","author":"S Khan","year":"2024","unstructured":"Khan S, AlQahtani SA, Noor S, Ahmad N (2024) PSSM-Sumo: deep learning based intelligent model for prediction of sumoylation sites using discriminative features. BMC Bioinformatics 25(1):284","journal-title":"BMC Bioinformatics"},{"issue":"7","key":"781_CR33","doi-asserted-by":"publisher","DOI":"10.3390\/app12073620","volume":"12","author":"S Lefkovits","year":"2022","unstructured":"Lefkovits S, Lefkovits L, Szil\u00e1gyi L (2022) HGG and LGG brain tumor segmentation in multi-modal MRI using pretrained convolutional neural networks of Amazon Sagemaker. Appl Sci 12(7):3620","journal-title":"Appl Sci"},{"key":"781_CR34","doi-asserted-by":"crossref","unstructured":"McIntyre L, Tuba E (2023) Brain tumor segmentation and classification using texture features and support vector machine. In 2023 11th International Symposium on Digital Forensics and Security (ISDFS) (pp. 1-5). IEEE","DOI":"10.1109\/ISDFS58141.2023.10131719"},{"key":"781_CR35","doi-asserted-by":"crossref","unstructured":"Mondal M, Faruk MF, Raihan N, Ahammed P (2021) Deep transfer learning based multi-class brain tumors classification using mri images. In 2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE) (pp. 73-76). IEEE","DOI":"10.1109\/ICEEE54059.2021.9719003"},{"key":"781_CR36","doi-asserted-by":"crossref","unstructured":"Nikhil SB, Nair NS, Challa NP, Katta R (2023) Classification and detection of brain tumors from magnetic resonance imaging scans using deep transfer-learning. In 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-7). IEEE","DOI":"10.1109\/ACCAI58221.2023.10200513"},{"issue":"1","key":"781_CR37","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-024-05978-1","volume":"25","author":"S Noor","year":"2024","unstructured":"Noor S, Naseem A, Awan HH, Aslam W, Khan S, AlQahtani SA, Ahmad N (2024) Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration. BMC Bioinformatics 25(1):360","journal-title":"BMC Bioinformatics"},{"issue":"3","key":"781_CR38","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00607-025-01441-y","volume":"107","author":"S Noor","year":"2025","unstructured":"Noor S, Awan HH, Hashmi AS, Saeed A, Khan S, AlQahtani SA (2025) Optimizing performance of parallel computing platforms for large-scale genome data analysis. Computing 107(3):1\u201322","journal-title":"Computing"},{"key":"781_CR39","doi-asserted-by":"crossref","unstructured":"Pamungkas Y, Triandini E, Yunanto W, Thwe Y (2025) Impact of Hyperparameter Tuning on ResNet-UNet Models for Enhanced Brain Tumor Segmentation in MRI Scans. International Journal of Robotics & Control Systems, 5(2)","DOI":"10.31763\/ijrcs.v5i2.1802"},{"key":"781_CR40","doi-asserted-by":"crossref","unstructured":"Polly FP, Shil SK, Hossain MA, Ayman A, Jang YM (2018) Detection and classification of HGG and LGG brain tumor using machine learning. In 2018 International Conference on Information Networking (ICOIN) (pp. 813-817). IEEE","DOI":"10.1109\/ICOIN.2018.8343231"},{"key":"781_CR41","doi-asserted-by":"crossref","unstructured":"Prakash RM, Kumari RSS (2019) Classification of MR brain images for detection of tumor with transfer learning from pre-trained CNN models. In 2019 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET) (pp. 508-511). IEEE","DOI":"10.1109\/WiSPNET45539.2019.9032811"},{"key":"781_CR42","doi-asserted-by":"crossref","unstructured":"Preetha R, Priyadarsini MJP, Nisha JS (2024) Automated brain tumor detection from magnetic resonance images using fine-tuned efficientnet-b4 convolutional neural network. IEEE Access","DOI":"10.1109\/ACCESS.2024.3442979"},{"issue":"28","key":"781_CR43","doi-asserted-by":"publisher","first-page":"36111","DOI":"10.1007\/s11042-021-11504-9","volume":"80","author":"HM Rai","year":"2021","unstructured":"Rai HM, Chatterjee K (2021) 2D MRI image analysis and brain tumor detection using deep learning CNN model LeU-Net. Multimedia Tools Appl 80(28):36111\u201336141","journal-title":"Multimedia Tools Appl"},{"issue":"1","key":"781_CR44","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1002\/jemt.23597","volume":"84","author":"A Rehman","year":"2021","unstructured":"Rehman A, Khan MA, Saba T, Mehmood Z, Tariq U, Ayesha N (2021) Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture. Microsc Res Tech 84(1):133\u2013149","journal-title":"Microsc Res Tech"},{"key":"781_CR45","doi-asserted-by":"crossref","unstructured":"Sasikumar P, Cherukuvada S, Balmurugan P, Anand PV, Brindasri S, Nareshkumar R (2024) An Efficient Brain tumor classification using CNN and transfer learning. In 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-5). IEEE","DOI":"10.1109\/ACCAI61061.2024.10602391"},{"key":"781_CR46","doi-asserted-by":"crossref","unstructured":"Sharma G, Jaswal G, Nigam A, Ramachandra R (2024) Fh-sstnet: Forehead creases based user verification using spatio-spatial temporal network. In 2024 12th International Workshop on Biometrics and Forensics (IWBF) (pp. 1-6). IEEE","DOI":"10.1109\/IWBF62628.2024.10593960"},{"key":"781_CR47","first-page":"1","volume":"2023","author":"M Uvaneshwari","year":"2023","unstructured":"Uvaneshwari M, Baskar M (2023) Machine Learning for Brain Tumour Detection: A Systematic Review of Segmentation and Classification Methods. Intelligent Computing and Control for Engineering and Business Systems (ICCEBS) 2023:1\u20137","journal-title":"Intelligent Computing and Control for Engineering and Business Systems (ICCEBS)"},{"key":"781_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.107960","volume":"101","author":"R Vankdothu","year":"2022","unstructured":"Vankdothu R, Hameed MA, Fatima H (2022) A brain tumor identification and classification using deep learning based on CNN-LSTM method. Comput Electr Eng 101:107960","journal-title":"Comput Electr Eng"},{"issue":"14","key":"781_CR49","doi-asserted-by":"publisher","first-page":"2593","DOI":"10.1080\/02664763.2016.1259399","volume":"44","author":"X Xu","year":"2017","unstructured":"Xu X (2017) Short-run price forecast performance of individual and composite models for 496 corn cash markets. J Appl Stat 44(14):2593\u20132620","journal-title":"J Appl Stat"},{"issue":"4","key":"781_CR50","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1002\/ajae.12041","volume":"102","author":"X Xu","year":"2020","unstructured":"Xu X (2020) Corn cash price forecasting. Am J Agr Econ 102(4):1297\u20131320","journal-title":"Am J Agr Econ"},{"key":"781_CR51","volume":"5","author":"X Xu","year":"2021","unstructured":"Xu X, Zhang Y (2021) Individual time series and composite forecasting of the Chinese stock index. Mach Learn Appl 5:100035","journal-title":"Mach Learn Appl"},{"key":"781_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.dajour.2023.100229","volume":"7","author":"X Xu","year":"2023","unstructured":"Xu X, Zhang Y (2023a) An integrated vector error correction and directed acyclic graph method for investigating contemporaneous causalities. Decis Anal J 7:100229","journal-title":"Decis Anal J"},{"key":"781_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.nexus.2023.100210","volume":"10","author":"X Xu","year":"2023","unstructured":"Xu X, Zhang Y (2023b) China mainland new energy index price forecasting with the neural network. Energy Nexus 10:100210","journal-title":"Energy Nexus"},{"key":"781_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.nexus.2023.100250","volume":"12","author":"X Xu","year":"2023","unstructured":"Xu X, Zhang Y (2023c) Edible oil wholesale price forecasts via the neural network. Energy Nexus 12:100250","journal-title":"Energy Nexus"},{"key":"781_CR55","doi-asserted-by":"publisher","first-page":"12","DOI":"10.12974\/2313-1047.2024.11.02","volume":"11","author":"H Yuanzhe","year":"2024","unstructured":"Yuanzhe H, Chengyi Q, Yuanjun W (2024) Preoperative grading of brain gliomas using 3D-ResNet18 based on multimodal MRI and attention mechanism. Journal of Psychology and Psychotherapy Research 11:12\u201320","journal-title":"Journal of Psychology and Psychotherapy Research"},{"issue":"13","key":"781_CR56","doi-asserted-by":"publisher","DOI":"10.7150\/jca.95987","volume":"15","author":"Y Zeng","year":"2024","unstructured":"Zeng Y, Liu N, Yang X, Huang C, Liu M (2024) Enhanced multimodal brain tumor classification in MR images using 2D ResNet as backbone with explicit tumor size information. J Cancer 15(13):4275","journal-title":"J Cancer"}],"container-title":["Network Modeling Analysis in Health Informatics and Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13721-026-00781-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13721-026-00781-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13721-026-00781-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T01:44:54Z","timestamp":1774057494000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13721-026-00781-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,21]]},"references-count":56,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["781"],"URL":"https:\/\/doi.org\/10.1007\/s13721-026-00781-9","relation":{},"ISSN":["2192-6670"],"issn-type":[{"value":"2192-6670","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,21]]},"assertion":[{"value":"27 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 January 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 February 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 March 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not Applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"101"}}