{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T14:46:22Z","timestamp":1782312382705,"version":"3.54.5"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Adv. Model. and Simul. in Eng. Sci."],"DOI":"10.1186\/s40323-026-00330-z","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T13:50:33Z","timestamp":1782309033000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A comprehensive study on estimating the primary crack spacing of flexural reinforced concrete components using machine learning techniques"],"prefix":"10.1186","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5607-9334","authenticated-orcid":false,"given":"Ahed","family":"Habib","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0102-8852","authenticated-orcid":false,"given":"Maan","family":"Habib","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0667-3148","authenticated-orcid":false,"given":"M. Talha","family":"Junaid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salah","family":"Altoubat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0657-0090","authenticated-orcid":false,"given":"Mohamed","family":"Maalej","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4234-0735","authenticated-orcid":false,"given":"Ausamah A. L.","family":"Houri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"issue":"2","key":"330_CR1","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1680\/stco.2005.6.2.53","volume":"6","author":"A Borosny\u00f3i","year":"2005","unstructured":"Borosny\u00f3i A, Bal\u00e1zs GL. Models for flexural cracking in concrete: the state of the art. Struct Concr. 2005;6(2):53\u201362. https:\/\/doi.org\/10.1680\/stco.2005.6.2.53.","journal-title":"Struct Concr"},{"issue":"2","key":"330_CR2","doi-asserted-by":"publisher","DOI":"10.1142\/S1793431123500021","volume":"17","author":"A Habib","year":"2023","unstructured":"Habib A, Yildirim U. Modeling reinforced concrete moment frames supported on quintuple friction pendulum bearings for nonlinear response history analysis. J Earthq Tsunami. 2023;17(2):2350002. https:\/\/doi.org\/10.1142\/S1793431123500021.","journal-title":"J Earthq Tsunami"},{"issue":"2","key":"330_CR3","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1108\/MMMS-08-2022-0158","volume":"19","author":"A Habib","year":"2023","unstructured":"Habib A, Yildirim U. Distribution of strong input energy in base-isolated structures with complex nonlinearity: a parametric assessment. Multidiscip Model Mater Struct. 2023;19(2):324\u201340. https:\/\/doi.org\/10.1108\/MMMS-08-2022-0158.","journal-title":"Multidiscip Model Mater Struct"},{"issue":"4","key":"330_CR4","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1680\/stco.2005.6.4.155","volume":"6","author":"AW Beeby","year":"2005","unstructured":"Beeby AW. The influence of the parameter \u03d5\/\u03c1 eff on crack widths. Struct Concr. 2005;6(4):155\u201365.","journal-title":"Struct Concr"},{"issue":"10","key":"330_CR5","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1680\/macr.2004.56.10.575","volume":"56","author":"G Kaklauskas","year":"2004","unstructured":"Kaklauskas G. Flexural layered deformational model of reinforced concrete members. Mag Concr Res. 2004;56(10):575\u201384. https:\/\/doi.org\/10.1680\/macr.2004.56.10.575.","journal-title":"Mag Concr Res"},{"key":"330_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-024-09497-2","author":"A Habib","year":"2024","unstructured":"Habib A, Barakat S, Al-Toubat S, Junaid MT, Maalej M. Developing machine learning models for identifying the failure potential of fire-exposed FRP-strengthened concrete beams. Arab J Sci Eng. 2024. https:\/\/doi.org\/10.1007\/s13369-024-09497-2.","journal-title":"Arab J Sci Eng"},{"key":"330_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.engfailanal.2022.106452","volume":"139","author":"U De Maio","year":"2022","unstructured":"De Maio U, Greco F, Leonetti L, Blasi PN, Pranno A. A cohesive fracture model for predicting crack spacing and crack width in reinforced concrete structures. Eng Fail Anal. 2022;139:106452. https:\/\/doi.org\/10.1016\/j.engfailanal.2022.106452.","journal-title":"Eng Fail Anal"},{"key":"330_CR8","doi-asserted-by":"crossref","unstructured":"Ng PL, Ma FJ, Kwan AKH. Crack analysis of concrete beams based on pseudo-discrete crack model. In Proceedings of the Second International Conference on Performance-Based and Life-Cycle Structural Engineering, Brisbane, Australia; 2015.","DOI":"10.14264\/uql.2016.1184"},{"issue":"1","key":"330_CR9","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1080\/13632469.2024.2409865","volume":"29","author":"A Habib","year":"2025","unstructured":"Habib A, Junaid MT, Dirar S, Barakat S, Al-Sadoon ZA. Machine learning-based estimation of reinforced concrete columns stiffness modifiers for improved accuracy in linear response history analysis. J Earthq Eng. 2025;29(1):130\u201355. https:\/\/doi.org\/10.1080\/13632469.2024.2409865.","journal-title":"J Earthq Eng"},{"key":"330_CR10","unstructured":"Borges JF. Cracking and deformability of reinforced concrete beams. Laborat\u00f3rio Nacional de Engenharia Civil; 1965."},{"issue":"10","key":"330_CR11","first-page":"1237","volume":"62","author":"BB Broms","year":"1965","unstructured":"Broms BB. Crack width and crack spacing in reinforced concrete members. J Proc. 1965;62(10):1237\u201356.","journal-title":"J Proc"},{"issue":"11","key":"330_CR12","first-page":"1395","volume":"62","author":"BB Broms","year":"1965","unstructured":"Broms BB, Lutz LA. Effects of arrangement of reinforcement on crack width and spacing of reinforced concrete members. J Proc. 1965;62(11):1395\u2013410.","journal-title":"J Proc"},{"key":"330_CR13","first-page":"87","volume":"20","author":"P Gergely","year":"1968","unstructured":"Gergely P, Lutz LA. Maximum crack width in reinforced concrete flexural members. American Concrete Institute. 1968;20:87\u2013117.","journal-title":"American Concrete Institute"},{"key":"330_CR14","unstructured":"Farra B, Jaccoud JP. Bond behaviour, tension stiffening and crack prediction of high-strength concrete. In Proceedings of the International Conference of Bond in Concrete, Riga, Latvia; 1992."},{"key":"330_CR15","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.cemconcomp.2018.04.012","volume":"99","author":"C Nader","year":"2019","unstructured":"Nader C, Rossi P, Tailhan JL. Multi-scale strategy for modeling macrocracks propagation in reinforced concrete structures. Cem Concr Compos. 2019;99:262\u201374. https:\/\/doi.org\/10.1016\/j.cemconcomp.2018.04.012.","journal-title":"Cem Concr Compos"},{"key":"330_CR16","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1016\/j.engfracmech.2018.12.006","volume":"206","author":"M Kurumatani","year":"2019","unstructured":"Kurumatani M, Soma Y, Terada K. Simulations of cohesive fracture behavior of reinforced concrete by a fracture-mechanics-based damage model. Eng Fract Mech. 2019;206:392\u2013407. https:\/\/doi.org\/10.1016\/j.engfracmech.2018.12.006.","journal-title":"Eng Fract Mech"},{"key":"330_CR17","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1016\/j.conbuildmat.2017.05.082","volume":"148","author":"JJ Wang","year":"2017","unstructured":"Wang JJ, Tao MX, Nie X. Fracture energy-based model for average crack spacing of reinforced concrete considering size effect and concrete strength variation. Constr Build Mater. 2017;148:398\u2013410. https:\/\/doi.org\/10.1016\/j.conbuildmat.2017.05.082.","journal-title":"Constr Build Mater"},{"issue":"4","key":"330_CR18","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1080\/15376494.2018.1472346","volume":"27","author":"DA Pozharskii","year":"2020","unstructured":"Pozharskii DA, Sobol BV, Vasiliev PV. Periodic crack system in a layered elastic wedge. Mech Adv Mater Struct. 2020;27(4):318\u201324. https:\/\/doi.org\/10.1080\/15376494.2018.1472346.","journal-title":"Mech Adv Mater Struct"},{"issue":"6","key":"330_CR19","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1016\/j.engstruct.2008.10.007","volume":"31","author":"G Kaklauskas","year":"2009","unstructured":"Kaklauskas G, Gribniak V, Bacinskas D, Vainiunas P. Shrinkage influence on tension stiffening in concrete members. Eng Struct. 2009;31(6):1305\u201312. https:\/\/doi.org\/10.1016\/j.engstruct.2008.10.007.","journal-title":"Eng Struct"},{"key":"330_CR20","unstructured":"Kaklauskas G, Ramanauskas R. A new approach in predicting the mean crack spacing of flexural reinforced concrete elements. In fib Symposium 2016, Performance-Based Approaches for Concrete Structures, Cape Town, South Africa; 2016."},{"key":"330_CR21","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1016\/j.engstruct.2017.07.090","volume":"150","author":"G Kaklauskas","year":"2017","unstructured":"Kaklauskas G, Ramanauskas R, Jakubovskis R. Mean crack spacing modelling for RC tension elements. Eng Struct. 2017;150:843\u201351. https:\/\/doi.org\/10.1016\/j.engstruct.2017.07.090.","journal-title":"Eng Struct"},{"issue":"5","key":"330_CR22","doi-asserted-by":"publisher","first-page":"422","DOI":"10.3846\/jcem.2019.9871","volume":"25","author":"G Kaklauskas","year":"2019","unstructured":"Kaklauskas G, Ramanauskas R, Ng PL. Predicting crack spacing of reinforced concrete tension members using strain compliance approach with debonding. J Civ Eng Manag. 2019;25(5):422\u201330. https:\/\/doi.org\/10.3846\/jcem.2019.9871.","journal-title":"J Civ Eng Manag"},{"key":"330_CR23","unstructured":"CEB-FIP. fib Model Code for Concrete Structures 2010. Ernst & Sohn; 2010"},{"key":"330_CR24","volume-title":"Eurocode 2: Design of concrete structures\u2014Part 1\u20131: General rules and rules for buildings","author":"Eurocode","year":"2004","unstructured":"Eurocode. Eurocode 2: Design of concrete structures\u2014Part 1\u20131: General rules and rules for buildings. British Standard Institution; 2004."},{"key":"330_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.conbuildmat.2023.130709","volume":"370","author":"KC Laxman","year":"2023","unstructured":"Laxman KC, Tabassum N, Ai L, Cole C, Ziehl P. Automated crack detection and crack depth prediction for reinforced concrete structures using deep learning. Constr Build Mater. 2023;370:130709. https:\/\/doi.org\/10.1016\/j.conbuildmat.2023.130709.","journal-title":"Constr Build Mater"},{"key":"330_CR26","doi-asserted-by":"publisher","first-page":"676","DOI":"10.1016\/j.engstruct.2013.03.020","volume":"52","author":"AA Elshafey","year":"2013","unstructured":"Elshafey AA, Dawood N, Marzouk H, Haddara M. Crack width in concrete using artificial neural networks. Eng Struct. 2013;52:676\u201386. https:\/\/doi.org\/10.1016\/j.engstruct.2013.03.020.","journal-title":"Eng Struct"},{"key":"330_CR27","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1016\/j.engfailanal.2013.02.011","volume":"31","author":"AA Elshafey","year":"2013","unstructured":"Elshafey AA, Dawood N, Marzouk H, Haddara M. Predicting of crack spacing for concrete by using neural networks. Eng Fail Anal. 2013;31:344\u201359. https:\/\/doi.org\/10.1016\/j.engfailanal.2013.02.011.","journal-title":"Eng Fail Anal"},{"issue":"15","key":"330_CR28","doi-asserted-by":"publisher","first-page":"2143","DOI":"10.1016\/j.engfracmech.2003.12.004","volume":"71","author":"R Ince","year":"2004","unstructured":"Ince R. Prediction of fracture parameters of concrete by artificial neural networks. Eng Fract Mech. 2004;71(15):2143\u201359. https:\/\/doi.org\/10.1016\/j.engfracmech.2003.12.004.","journal-title":"Eng Fract Mech"},{"key":"330_CR29","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1016\/j.engfracmech.2017.11.010","volume":"186","author":"IM Nikbin","year":"2017","unstructured":"Nikbin IM, Rahimi S, Allahyari H. A new empirical formula for prediction of fracture energy of concrete based on the artificial neural network. Eng Fract Mech. 2017;186:466\u201382. https:\/\/doi.org\/10.1016\/j.engfracmech.2017.11.010.","journal-title":"Eng Fract Mech"},{"key":"330_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.engstruct.2021.112377","volume":"241","author":"PN Pizarro","year":"2021","unstructured":"Pizarro PN, Massone LM. Structural design of reinforced concrete buildings based on deep neural networks. Eng Struct. 2021;241:112377. https:\/\/doi.org\/10.1016\/j.engstruct.2021.112377.","journal-title":"Eng Struct"},{"key":"330_CR31","doi-asserted-by":"publisher","first-page":"899","DOI":"10.1016\/j.istruc.2022.10.103","volume":"46","author":"T Nguyen","year":"2022","unstructured":"Nguyen T, Truong TT, Nguyen-Thoi T, Bui LVH, Nguyen TH. Evaluation of residual flexural strength of corroded reinforced concrete beams using convolutional long short-term memory neural networks. Structures. 2022;46:899\u2013912. https:\/\/doi.org\/10.1016\/j.istruc.2022.10.103.","journal-title":"Structures"},{"key":"330_CR32","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1016\/j.conbuildmat.2018.08.011","volume":"186","author":"S Dorafshan","year":"2018","unstructured":"Dorafshan S, Thomas RJ, Maguire M. Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete. Constr Build Mater. 2018;186:1031\u201345. https:\/\/doi.org\/10.1016\/j.conbuildmat.2018.08.011.","journal-title":"Constr Build Mater"},{"key":"330_CR33","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.autcon.2018.11.028","volume":"99","author":"CV Dung","year":"2019","unstructured":"Dung CV. Autonomous concrete crack detection using deep fully convolutional neural network. Autom Constr. 2019;99:52\u20138. https:\/\/doi.org\/10.1016\/j.autcon.2018.11.028.","journal-title":"Autom Constr"},{"key":"330_CR34","doi-asserted-by":"crossref","unstructured":"Moon HG, Kim JH. Intelligent crack detecting algorithm on the concrete crack image using neural network. In Proceedings of the 28th ISARC; 2011.","DOI":"10.22260\/ISARC2011\/0279"},{"issue":"1","key":"330_CR35","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1080\/15376494.2020.1751352","volume":"29","author":"R Ramanauskas","year":"2022","unstructured":"Ramanauskas R, Kaklauskas G, Sokolov A. Estimating the primary crack spacing of reinforced concrete structures: predictions by neural network versus the innovative strain compliance approach. Mech Adv Mater Struct. 2022;29(1):53\u201369. https:\/\/doi.org\/10.1080\/15376494.2020.1751352.","journal-title":"Mech Adv Mater Struct"},{"key":"330_CR36","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1016\/j.conbuildmat.2019.04.227","volume":"215","author":"G Bayar","year":"2019","unstructured":"Bayar G, Bilir T. A novel study for the estimation of crack propagation in concrete using machine learning algorithms. Constr Build Mater. 2019;215:670\u201385. https:\/\/doi.org\/10.1016\/j.conbuildmat.2019.04.227.","journal-title":"Constr Build Mater"},{"issue":"3","key":"330_CR37","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1177\/1475921718768747","volume":"18","author":"H Kim","year":"2019","unstructured":"Kim H, Ahn E, Shin M, Sim SH. Crack and noncrack classification from concrete surface images using machine learning. Struct Health Monit. 2019;18(3):725\u201338. https:\/\/doi.org\/10.1177\/1475921718768747.","journal-title":"Struct Health Monit"},{"issue":"1","key":"330_CR38","doi-asserted-by":"publisher","DOI":"10.1515\/cls-2022-0194","volume":"10","author":"O Alomari","year":"2023","unstructured":"Alomari O, Al-Rawashdeh M. Application of soft computing in estimating primary crack spacing of reinforced concrete structures. Curved Layered Struct. 2023;10(1):20220194. https:\/\/doi.org\/10.1515\/cls-2022-0194.","journal-title":"Curved Layered Struct"},{"issue":"1","key":"330_CR39","doi-asserted-by":"publisher","DOI":"10.1007\/s43621-024-00500-2","volume":"5","author":"M Habib","year":"2024","unstructured":"Habib M, Habib A, Albzaie M, Farghal A. Sustainability benefits of AI-based engineering solutions for infrastructure resilience in arid regions against extreme rainfall events. Discov Sustain. 2024;5(1):278. https:\/\/doi.org\/10.1007\/s43621-024-00500-2.","journal-title":"Discov Sustain"},{"issue":"8","key":"330_CR40","doi-asserted-by":"publisher","first-page":"3129","DOI":"10.1108\/EC-09-2021-0527","volume":"39","author":"A Habib","year":"2022","unstructured":"Habib A, Yildirim U. Estimating mechanical and dynamic properties of rubberized concrete using machine learning techniques: a comprehensive study. Eng Comput. 2022;39(8):3129\u201378. https:\/\/doi.org\/10.1108\/EC-09-2021-0527.","journal-title":"Eng Comput"},{"issue":"5","key":"330_CR41","doi-asserted-by":"publisher","first-page":"1370","DOI":"10.28991\/CEJ-2024-010-05-02","volume":"10","author":"M Shrif","year":"2024","unstructured":"Shrif M, Al-Sadoon ZA, Barakat S, Habib A, Mostafa O. Optimizing gene expression programming to predict shear capacity in corrugated web steel beams. Civil Eng J. 2024;10(5):1370\u201385. https:\/\/doi.org\/10.28991\/CEJ-2024-010-05-02.","journal-title":"Civil Eng J"},{"key":"330_CR42","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-024-08776-2","author":"M Habib","year":"2024","unstructured":"Habib M, Okayli M. Evaluating the sensitivity of machine learning models to data preprocessing technique in concrete compressive strength estimation. Arab J Sci Eng. 2024. https:\/\/doi.org\/10.1007\/s13369-024-08776-2.","journal-title":"Arab J Sci Eng"},{"issue":"9","key":"330_CR43","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)ST.1943-541X.0001842","volume":"143","author":"G Kaklauskas","year":"2017","unstructured":"Kaklauskas G. Crack model for RC members based on compatibility of stress-transfer and mean-strain approaches. J Struct Eng. 2017;143(9):04017105. https:\/\/doi.org\/10.1061\/(ASCE)ST.1943-541X.0001842.","journal-title":"J Struct Eng"},{"issue":"347","key":"330_CR44","doi-asserted-by":"publisher","first-page":"e289","DOI":"10.3989\/mc.2022.13621","volume":"72","author":"A Habib","year":"2022","unstructured":"Habib A, Yildirim U. Simplified modeling of rubberized concrete properties using multivariable regression analysis. Mater Construcc. 2022;72(347):e289\u2013e289. https:\/\/doi.org\/10.3989\/mc.2022.13621.","journal-title":"Mater Construcc"},{"issue":"4","key":"330_CR45","doi-asserted-by":"publisher","first-page":"5383","DOI":"10.1007\/s13369-022-07435-8","volume":"48","author":"A Habib","year":"2023","unstructured":"Habib A, Yildirim U, Habib M. Applying Kernel principal component analysis for enhanced multivariable regression modeling of rubberized concrete properties. Arab J Sci Eng. 2023;48(4):5383\u201396. https:\/\/doi.org\/10.1007\/s13369-022-07435-8.","journal-title":"Arab J Sci Eng"},{"issue":"1","key":"330_CR46","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-69271-0","volume":"14","author":"WB Inqiad","year":"2024","unstructured":"Inqiad WB, Javed MF, Onyelowe K, Siddique MS, Asif U, Alkhattabi L, et al. Soft computing models for prediction of bentonite plastic concrete strength. Sci Rep. 2024;14(1):18145.","journal-title":"Sci Rep"},{"key":"330_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.istruc.2025.108802","volume":"76","author":"WB Inqiad","year":"2025","unstructured":"Inqiad WB, Khan MS, Alarifi SS. Reliable determination of peak shear strength of H-shaped concrete squat walls using explainable machine learning techniques. Structures. 2025;76:108802.","journal-title":"Structures"},{"issue":"5","key":"330_CR48","first-page":"592","volume":"88","author":"KH Reineck","year":"1991","unstructured":"Reineck KH. Ultimate shear force of structural concrete members without transverse reinforcement derived from a mechanical model. ACI Struct J. 1991;88(5):592\u2013602.","journal-title":"ACI Struct J"}],"container-title":["Advanced Modeling and Simulation in Engineering Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40323-026-00330-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40323-026-00330-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40323-026-00330-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T13:50:44Z","timestamp":1782309044000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s40323-026-00330-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,24]]},"references-count":48,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["330"],"URL":"https:\/\/doi.org\/10.1186\/s40323-026-00330-z","relation":{},"ISSN":["2213-7467"],"issn-type":[{"value":"2213-7467","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,24]]},"assertion":[{"value":"17 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2026","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.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors hereby provide their consent for the publication of this manuscript in the journal.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"12"}}