{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T09:00:09Z","timestamp":1766221209097,"version":"3.48.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T00:00:00Z","timestamp":1766188800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T00:00:00Z","timestamp":1766188800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Princess Nourah Bint Abdulrahman University,Saudi Arabia","award":["PNURSP2025R384"],"award-info":[{"award-number":["PNURSP2025R384"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Computing"],"DOI":"10.1007\/s10791-025-09865-y","type":"journal-article","created":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T08:57:03Z","timestamp":1766221023000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhanced fingerprint matching using convolutional neural network and MultiHead self attention"],"prefix":"10.1007","volume":"28","author":[{"given":"Syeda Fatima Zohra","family":"Sajjad","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bushra","family":"Zafar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nouman","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdul","family":"Rehman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yazeed Yasin","family":"Ghadi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hend Khalid","family":"Alkahtani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,20]]},"reference":[{"issue":"1","key":"9865_CR1","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/TCSVT.2003.818349","volume":"14","author":"AK Jain","year":"2004","unstructured":"Jain AK, Ross A, Prabhakar S. An introduction to biometric recognition. IEEE Trans Circuits Syst Video Technol. 2004;14(1):4\u201320.","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"7","key":"9865_CR2","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.3390\/sym17071002","volume":"17","author":"H Song","year":"2025","unstructured":"Song H, Xie J, Liang L, Su Y, Xiao Y, Zhang X, et al. Symmetrical learning and transferring: efficient knowledge distillation for remote sensing image classification. Symmetry. 2025;17(7):1002.","journal-title":"Symmetry"},{"issue":"6","key":"9865_CR3","doi-asserted-by":"publisher","first-page":"7541","DOI":"10.1007\/s10586-024-04352-3","volume":"27","author":"O Aiadi","year":"2024","unstructured":"Aiadi O, Khaldi B, Korichi A, Chaa M, Bezziane MB, Omara I. Fusion of deep and local gradient-based features for multimodal finger knuckle print identification. Clust Comput. 2024;27(6):7541\u201357.","journal-title":"Clust Comput"},{"issue":"12","key":"9865_CR4","doi-asserted-by":"publisher","first-page":"8515","DOI":"10.1016\/j.asr.2025.04.009","volume":"75","author":"H Song","year":"2025","unstructured":"Song H, Xie J, Duan Y, Xie X, Zhou Y, Wang W. Cmkd-net: a cross-modal knowledge distillation method for remote sensing image classification. Adv Space Res. 2025;75(12):8515\u201334.","journal-title":"Adv Space Res"},{"issue":"2","key":"9865_CR5","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3390\/inventions7020039","volume":"7","author":"A-M Dincua","year":"2022","unstructured":"Dincua A-M, Moldovanu S, Moraru L. A fingerprint matching algorithm using the combination of edge features and convolution neural networks. Inventions. 2022;7(2):39.","journal-title":"Inventions"},{"issue":"4","key":"9865_CR6","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/s11265-023-01870-y","volume":"95","author":"H Shafaghi","year":"2023","unstructured":"Shafaghi H, Kiani M, Amirany A, Jafari K, Moaiyeri MH. A fast and light fingerprint-matching model based on deep learning approaches. J Signal Process Syst. 2023;95(4):551\u20138.","journal-title":"J Signal Process Syst"},{"issue":"33","key":"9865_CR7","doi-asserted-by":"publisher","first-page":"80201","DOI":"10.1007\/s11042-024-18918-1","volume":"83","author":"AK Dutta","year":"2024","unstructured":"Dutta AK, Raparthi M, Alsaadi M, Bhatt MW, Dodda SB, Sandhu M, et al. Deep learning-based multi-head self-attention model for human epilepsy identification from eeg signal for biomedical traits. Multimed Tools Appl. 2024;83(33):80201\u201323.","journal-title":"Multimed Tools Appl"},{"issue":"189","key":"9865_CR8","doi-asserted-by":"publisher","first-page":"70004","DOI":"10.1111\/phor.70004","volume":"40","author":"H Song","year":"2025","unstructured":"Song H, Xie J, Wang Y, Fu L, Zhou Y, Zhou X. Optimized data distribution learning for enhancing vision transformer-based object detection in remote sensing images. Photogram Rec. 2025;40(189):70004.","journal-title":"Photogram Rec"},{"issue":"1","key":"9865_CR9","doi-asserted-by":"publisher","first-page":"0296270","DOI":"10.1371\/journal.pone.0296270","volume":"19","author":"N Yadav","year":"2024","unstructured":"Yadav N, Mudgal D, Mishra A, Shukla S, Malik T, Mishra V. Harnessing fluorescent carbon quantum dots from natural resource for advancing sweat latent fingerprint recognition with machine learning algorithms for enhanced human identification. PLoS ONE. 2024;19(1):0296270.","journal-title":"PLoS ONE"},{"key":"9865_CR10","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2021.655486","volume":"4","author":"A Adensamer","year":"2021","unstructured":"Adensamer A, Klausner LD. Part man, part machine, all cop: automation in policing. Front Artif Intell. 2021;4:655486.","journal-title":"Front Artif Intell"},{"key":"9865_CR11","unstructured":"Grosz SA, Engelsma JJ, Ranjan R, Ramakrishnan N, Aggarwal M, Medioni GG, Jain AK. Minutiae-guided fingerprint embeddings via vision transformers. arXiv preprint arXiv:2210.13994 2022."},{"issue":"1","key":"9865_CR12","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/TBIOM.2023.3317303","volume":"6","author":"SA Grosz","year":"2023","unstructured":"Grosz SA, Jain AK. Afr-net: attention-driven fingerprint recognition network. IEEE Trans Biom Behav Identity Sci. 2023;6(1):30\u201342.","journal-title":"IEEE Trans Biom Behav Identity Sci"},{"key":"9865_CR13","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.seizure.2023.03.011","volume":"107","author":"D Norata","year":"2023","unstructured":"Norata D, Broggi S, Alvisi L, Lattanzi S, Brigo F, Tinuper P, et al. The eeg pen-on-paper sound: history and recent advances. Seizure Eur J Epilepsy. 2023;107:67\u201370.","journal-title":"Seizure Eur J Epilepsy"},{"issue":"3","key":"9865_CR14","first-page":"3003","volume":"142","author":"M Singh","year":"2025","unstructured":"Singh M, Singla S. Efi-satl: an efficientnet and self-attention based biometric recognition for finger-vein using deep transfer learning. Comput Model Eng Sci. 2025;142(3):3003.","journal-title":"Comput Model Eng Sci"},{"key":"9865_CR15","unstructured":"Tan M, Le Q. Efficientnet: Rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning, 2019. pp. 6105\u20136114. PMLR."},{"issue":"186","key":"9865_CR16","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1111\/phor.12489","volume":"39","author":"H Song","year":"2024","unstructured":"Song H, Yuan Y, Ouyang Z, Yang Y, Xiang H. Quantitative regularization in robust vision transformer for remote sensing image classification. Photogram Rec. 2024;39(186):340\u201372.","journal-title":"Photogram Rec"},{"issue":"1","key":"9865_CR17","doi-asserted-by":"publisher","first-page":"5507","DOI":"10.1038\/s41598-025-89735-1","volume":"15","author":"H Song","year":"2025","unstructured":"Song H, Xie H, Duan Y, Xie X, Gan F, Wang W, et al. Pure data correction enhancing remote sensing image classification with a lightweight ensemble model. Sci Rep. 2025;15(1):5507.","journal-title":"Sci Rep"},{"key":"9865_CR18","doi-asserted-by":"crossref","unstructured":"Tang Y, Gao F, Feng J, Liu Y. Fingernet: An unified deep network for fingerprint minutiae extraction. In: 2017 IEEE International Joint Conference on Biometrics (IJCB), 2017. pp. 108\u2013116. IEEE.","DOI":"10.1109\/BTAS.2017.8272688"},{"key":"9865_CR19","doi-asserted-by":"crossref","unstructured":"Song D, Feng J. Fingerprint indexing based on pyramid deep convolutional feature. In: 2017 IEEE International Joint Conference on Biometrics (IJCB), 2017. pp. 200\u2013207. IEEE.","DOI":"10.1109\/BTAS.2017.8272699"},{"key":"9865_CR20","doi-asserted-by":"crossref","unstructured":"Michelsanti D, Ene A-D, Guichi Y, Stef R, Nasrollahi K, Moeslund TB. Fast fingerprint classification with deep neural networks. In: International Conference on Computer Vision Theory and Applications, 2017. vol. 6, pp. 202\u2013209. Scitepress.","DOI":"10.5220\/0006116502020209"},{"key":"9865_CR21","doi-asserted-by":"crossref","unstructured":"Shrein JM Fingerprint classification using convolutional neural networks and ridge orientation images. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017. pp. 1\u20138. IEEE.","DOI":"10.1109\/SSCI.2017.8285375"},{"key":"9865_CR22","doi-asserted-by":"publisher","first-page":"113","DOI":"10.3389\/frobt.2020.00113","volume":"7","author":"UU Deshpande","year":"2020","unstructured":"Deshpande UU, Malemath V, Patil SM, Chaugule SV. Cnnai: a convolution neural network-based latent fingerprint matching using the combination of nearest neighbor arrangement indexing. Front Robot AI. 2020;7:113.","journal-title":"Front Robot AI"},{"key":"9865_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2021.107387","volume":"95","author":"M Ahsan","year":"2021","unstructured":"Ahsan M, Based M, Haider J, Kowalski M, et al. An intelligent system for automatic fingerprint identification using feature fusion by gabor filter and deep learning. Comput Electr Eng. 2021;95:107387.","journal-title":"Comput Electr Eng"},{"key":"9865_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/5545488","volume":"2021","author":"JK Appati","year":"2021","unstructured":"Appati JK, Nartey PK, Owusu E, Denwar IW. Implementation of a transform-minutiae fusion-based model for fingerprint recognition. Int J Math Math Sci. 2021;2021:1\u201312.","journal-title":"Int J Math Math Sci"},{"issue":"17","key":"9865_CR25","doi-asserted-by":"publisher","first-page":"24515","DOI":"10.1007\/s11042-022-12294-4","volume":"81","author":"P Nahar","year":"2022","unstructured":"Nahar P, Chaudhari NS, Tanwani SK. Fingerprint classification system using cnn. Multimed Tools Appl. 2022;81(17):24515\u201327.","journal-title":"Multimed Tools Appl"},{"issue":"4","key":"9865_CR26","first-page":"1703","volume":"39","author":"DS Ametefe","year":"2023","unstructured":"Ametefe DS, Sarnin SS, Ali DM, Muhammad ZZ. Fingerprint pattern classification using deep transfer learning and data augmentation. Vis Comput. 2023;39(4):1703\u201316.","journal-title":"Vis Comput"},{"key":"9865_CR27","doi-asserted-by":"crossref","unstructured":"Farag R, Upadhay P, Dembys J, Gao Y, Montoya KG, Tousi SMA, Omotara G, Desouza G. Efficientnet-sam: A novel effecientnet with spatial attention mechanism for covid-19 detection in pulmonary ct scans. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024. pp. 5200\u20135206.","DOI":"10.1109\/CVPRW63382.2024.00528"},{"key":"9865_CR28","unstructured":"Zhong Y, Deng W. Face transformer for recognition. arXiv preprint arXiv:2103.14803 2021."},{"key":"9865_CR29","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1109\/LSP.2025.3542336","volume":"32","author":"E Li","year":"2025","unstructured":"Li E, Yang L, Su K, Liu H. Local and global feature interaction network for partial finger vein recognition. IEEE Signal Process Lett. 2025;32:906\u201310.","journal-title":"IEEE Signal Process Lett"},{"issue":"26","key":"9865_CR30","doi-asserted-by":"publisher","first-page":"31239","DOI":"10.1007\/s11042-024-20396-4","volume":"84","author":"P Kaplesh","year":"2025","unstructured":"Kaplesh P, Gupta A, Bansal D, Sofat S, Mittal A. Vision transformer for contactless fingerprint classification. Multimed Tools Appl. 2025;84(26):31239\u201359.","journal-title":"Multimed Tools Appl"},{"issue":"4","key":"9865_CR31","doi-asserted-by":"publisher","first-page":"25618","DOI":"10.48084\/etasr.11468","volume":"15","author":"M Bahaa","year":"2025","unstructured":"Bahaa M, Aloufi FA. Enhanced-typenet for biometric keystroke authentication using key embedding. Eng Technol Appl Sci Res. 2025;15(4):25618\u201326.","journal-title":"Eng Technol Appl Sci Res"},{"issue":"2","key":"9865_CR32","first-page":"37","volume":"2","author":"N Kumar","year":"2012","unstructured":"Kumar N, Verma P. Fingerprint image enhancement and minutia matching. Int J Eng Sci Emerg Technol. 2012;2(2):37\u201342.","journal-title":"Int J Eng Sci Emerg Technol"},{"key":"9865_CR33","doi-asserted-by":"crossref","unstructured":"Wang X, Yu K, Wu S, Gu J, Liu Y, Dong C, Qiao Y, Change\u00a0Loy C. Esrgan: enhanced super-resolution generative adversarial networks. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018. pp. 0\u20130.","DOI":"10.1007\/978-3-030-11021-5_5"},{"issue":"1","key":"9865_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-019-0197-0","volume":"6","author":"C Shorten","year":"2019","unstructured":"Shorten C, Khoshgoftaar TM. A survey on image data augmentation for deep learning. J Big Data. 2019;6(1):1\u201348.","journal-title":"J Big Data"},{"issue":"5","key":"9865_CR35","doi-asserted-by":"publisher","first-page":"2463","DOI":"10.12928\/telkomnika.v18i5.16717","volume":"18","author":"TS Gunawan","year":"2020","unstructured":"Gunawan TS, Ashraf A, Riza BS, Haryanto EV, Rosnelly R, Kartiwi M, et al. Development of video-based emotion recognition using deep learning with google colab. TELKOMNIKA (Telecommun Comput Electron Control). 2020;18(5):2463\u201371.","journal-title":"TELKOMNIKA (Telecommun Comput Electron Control)"},{"key":"9865_CR36","unstructured":"BioLab: FVC2000. http:\/\/bias.csr.unibo.it\/fvc2000\/databases.asp"},{"key":"9865_CR37","unstructured":"BioLab: FVC2002. http:\/\/bias.csr.unibo.it\/fvc2002\/databases.asp"},{"key":"9865_CR38","unstructured":"BioLab: FVC2004. http:\/\/bias.csr.unibo.it\/fvc2004\/databases.asp"},{"key":"9865_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.sasc.2024.200106","volume":"6","author":"R Garg","year":"2024","unstructured":"Garg R, Singh G, Singh A, Singh MP. Fingerprint recognition using convolution neural network with inversion and augmented techniques. Syst Soft Comput. 2024;6:200106.","journal-title":"Syst Soft Comput"},{"key":"9865_CR40","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1007\/s10489-019-01530-4","volume":"50","author":"Y Liu","year":"2020","unstructured":"Liu Y, Zhou B, Han C, Guo T, Qin J. A novel method based on deep learning for aligned fingerprints matching. Appl Intell. 2020;50:397\u2013416.","journal-title":"Appl Intell"},{"key":"9865_CR41","first-page":"1","volume":"17","author":"PE Gundgurti","year":"2024","unstructured":"Gundgurti PE, Kulkarni SB. An effective finger-print validation and identification using a-kaze and surf algorithm. Int J Intell Eng Syst. 2024;17:1.","journal-title":"Int J Intell Eng Syst"},{"key":"9865_CR42","doi-asserted-by":"crossref","unstructured":"Omar SS, Ahmed WS, Ismail MN, Sieliukov O. In-depth examination of a fingerprint recognition system using the gabor filter. In: 2024 35th Conference of Open Innovations Association (FRUCT), 2024. pp. 532\u2013543. IEEE","DOI":"10.23919\/FRUCT61870.2024.10516364"},{"issue":"3","key":"9865_CR43","doi-asserted-by":"publisher","first-page":"211","DOI":"10.54287\/gujsa.1077430","volume":"9","author":"A Iorliam","year":"2022","unstructured":"Iorliam A, Orgem E, Shehu YI. An investigation of benford\u2019s law divergence and machine learning techniques for intra-class separability of fingerprint images. Gazi Univ J Sci Part A Eng Innov. 2022;9(3):211\u201324.","journal-title":"Gazi Univ J Sci Part A Eng Innov"},{"issue":"15","key":"9865_CR44","doi-asserted-by":"publisher","first-page":"22795","DOI":"10.1007\/s11042-023-14576-x","volume":"82","author":"EU Sehar","year":"2023","unstructured":"Sehar EU, Selwal A, Sharma D. Fincat: a novel approach for fingerprint template protection using quadrant mapping via non-invertible transformation. Multimed Tools Appl. 2023;82(15):22795\u2013813.","journal-title":"Multimed Tools Appl"},{"issue":"4","key":"9865_CR45","doi-asserted-by":"publisher","first-page":"2028","DOI":"10.3390\/app12042028","volume":"12","author":"S Bakheet","year":"2022","unstructured":"Bakheet S, Al-Hamadi A, Youssef R. A fingerprint-based verification framework using harris and surf feature detection algorithms. Appl Sci. 2022;12(4):2028.","journal-title":"Appl Sci"},{"key":"9865_CR46","doi-asserted-by":"crossref","unstructured":"Maheta S et al. Cancelable biometric recognition using deep learning based resnet50 model. In: 2023 IEEE Guwahati Subsection Conference (GCON), 2023. pp. 01\u201306. IEEE.","DOI":"10.1109\/GCON58516.2023.10183603"},{"key":"9865_CR47","unstructured":"Alimovski E, Rasheed J, Tilki S. Automated biometrical fingerprint recognition scheme using synthesized images 2024."},{"key":"9865_CR48","doi-asserted-by":"crossref","unstructured":"Ali A, Khan R, Ullah I, Khan AD, Munir A. Minutiae based automatic fingerprint recognition: Machine learning approaches. In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 2015. pp. 1148\u20131153. IEEE.","DOI":"10.1109\/CIT\/IUCC\/DASC\/PICOM.2015.171"},{"issue":"2","key":"9865_CR49","first-page":"1025","volume":"14","author":"UU Deshpande","year":"2022","unstructured":"Deshpande UU, Malemath V, Patil SM, Chaugule SV. Automatic latent fingerprint identification system using scale and rotation invariant minutiae features. Int J Inf Technol. 2022;14(2):1025\u201339.","journal-title":"Int J Inf Technol"},{"issue":"8","key":"9865_CR50","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.3390\/math10081285","volume":"10","author":"F Saeed","year":"2022","unstructured":"Saeed F, Hussain M, Aboalsamh HA. Automatic fingerprint classification using deep learning technology (deepfktnet). Mathematics. 2022;10(8):1285.","journal-title":"Mathematics"},{"key":"9865_CR51","first-page":"2","volume":"50","author":"M Kumar","year":"2023","unstructured":"Kumar M, Kumar D. An efficient gravitational search decision forest approach for fingerprint recognition. Kuwait J Sci. 2023;50:2.","journal-title":"Kuwait J Sci"},{"key":"9865_CR52","doi-asserted-by":"crossref","unstructured":"Nguyen D-L, Cao K, Jain AK. Robust minutiae extractor: Integrating deep networks and fingerprint domain knowledge. In: 2018 International Conference on Biometrics (ICB), 2018. pp. 9\u201316. IEEE.","DOI":"10.1109\/ICB2018.2018.00013"},{"key":"9865_CR53","doi-asserted-by":"crossref","unstructured":"Ghaddab MH, Jouini K, Korbaa O. Fast and accurate fingerprint matching using expanded delaunay triangulation. In: 2017 IEEE\/ACS 14th International Conference on Computer Systems and Applications (AICCSA), 2017. pp. 751\u2013758. IEEE.","DOI":"10.1109\/AICCSA.2017.33"},{"key":"9865_CR54","doi-asserted-by":"crossref","unstructured":"Bakhshi B, Veisi H. End to end fingerprint verification based on convolutional neural network. In: 2019 27th Iranian Conference on Electrical Engineering (ICEE), 2019. pp. 1994\u20131998. IEEE.","DOI":"10.1109\/IranianCEE.2019.8786720"},{"key":"9865_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115832","volume":"186","author":"AK Trivedi","year":"2021","unstructured":"Trivedi AK, Thounaojam DM, Pal S. A novel minutiae triangulation technique for non-invertible fingerprint template generation. Exp Syst Appl. 2021;186:115832.","journal-title":"Exp Syst Appl"},{"issue":"4","key":"9865_CR56","doi-asserted-by":"publisher","first-page":"4073","DOI":"10.1007\/s13369-021-05390-4","volume":"46","author":"Y Surajkanta","year":"2021","unstructured":"Surajkanta Y, Pal S. A digital geometry-based fingerprint matching technique. Arab J Sci Eng. 2021;46(4):4073\u201386.","journal-title":"Arab J Sci Eng"},{"issue":"12","key":"9865_CR57","doi-asserted-by":"publisher","first-page":"6122","DOI":"10.3390\/app12126122","volume":"12","author":"S Bakheet","year":"2022","unstructured":"Bakheet S, Alsubai S, Alqahtani A, Binbusayyis A. Robust fingerprint minutiae extraction and matching based on improved sift features. Appl Sci. 2022;12(12):6122.","journal-title":"Appl Sci"}],"container-title":["Discover Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10791-025-09865-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10791-025-09865-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10791-025-09865-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T08:57:09Z","timestamp":1766221029000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10791-025-09865-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,20]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["9865"],"URL":"https:\/\/doi.org\/10.1007\/s10791-025-09865-y","relation":{},"ISSN":["2948-2992"],"issn-type":[{"value":"2948-2992","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,20]]},"assertion":[{"value":"6 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 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":"Not applicable. This study did not involve any human participants, animals, or clinical procedures requiring ethical review.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable. This article does not contain any individual personal data.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"314"}}