{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T19:07:06Z","timestamp":1793300826004,"version":"4.5.0"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001711","name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","doi-asserted-by":"publisher","award":["200021 204316"],"award-info":[{"award-number":["200021 204316"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Exp Mech"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Determining accurate constitutive laws from experimental data remains a key challenge in mechanics, particularly when the material behavior is nonlinear and the dataset is limited or noisy. Traditional approaches rely on identifying parameters of preselected material models, which separates the model selection and the calibration tasks leading to a potentially long and tedious trial-and-error procedure.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This work aims to assess the performance of EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), a recently proposed framework for automated discovery of constitutive laws, when applied to experimental data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Mechanical tests are conducted on natural rubber specimens of varying geometrical complexity. Both global (force\u2013elongation) and local (full-field displacement) data are collected. Constitutive laws are obtained via two routes: (i) conventional parameter identification in a priori selected models, and (ii) EUCLID, which integrates model selection and parameter identification in a unified model discovery pipeline.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The two approaches are compared in terms of predictive accuracy, generalization to unseen geometries, and robustness to experimental noise. The coverage of the material state space achieved by each dataset is quantified, and the relative performance of different datasets and models is analyzed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>EUCLID enables automated and data-driven discovery of constitutive laws, offering improved flexibility compared to conventional identification methods, and showing strong potential for reliable material modeling based on experimental data.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11340-026-01290-6","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T17:12:18Z","timestamp":1776791538000},"page":"877-908","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Discovery of Hyperelastic Constitutive Laws from Experimental Data with EUCLID"],"prefix":"10.1007","volume":"66","author":[{"given":"A.","family":"Abbasi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Ricci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P.","family":"Carrara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Flaschel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Marfia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2748-3287","authenticated-orcid":false,"given":"L.","family":"De Lorenzis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,21]]},"reference":[{"issue":"6","key":"1290_CR1","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1007\/s00466-004-0593-y","volume":"34","author":"RW Ogden","year":"2004","unstructured":"Ogden RW, Saccomandi G, Sgura I (2004) Fitting hyperelastic models to experimental data. Comput Mech 34(6):484\u2013502. https:\/\/doi.org\/10.1007\/s00466-004-0593-y","journal-title":"Comput Mech"},{"key":"1290_CR2","doi-asserted-by":"publisher","unstructured":"Marckmann G, Verron E (2006) Comparison of Hyperelastic Models for Rubber-Like Materials. Rubber Chem Technol 79(5):835\u2013858. https:\/\/doi.org\/10.5254\/1.3547969. https:\/\/meridian.allenpress.com\/rct\/article\/79\/5\/835\/93139\/Comparison-of-Hyperelastic-Models-for-RubberLike","DOI":"10.5254\/1.3547969"},{"key":"1290_CR3","doi-asserted-by":"publisher","unstructured":"Ricker A, Wriggers P (2023) Systematic fitting and comparison of hyperelastic continuum models for elastomers, Vol 30, Springer, Netherlands. https:\/\/doi.org\/10.1007\/s11831-022-09865-x","DOI":"10.1007\/s11831-022-09865-x"},{"issue":"9","key":"1290_CR4","doi-asserted-by":"publisher","first-page":"582","DOI":"10.1063\/1.1712836","volume":"11","author":"M Mooney","year":"1940","unstructured":"Mooney M (1940) A theory of large elastic deformation. J Appl Phys 11(9):582\u2013592. https:\/\/doi.org\/10.1063\/1.1712836","journal-title":"J Appl Phys"},{"issue":"835","key":"1290_CR5","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1098\/rsta.1948.0024","volume":"241","author":"RS Rivlin","year":"1948","unstructured":"Rivlin RS (1948) Large elastic deformations of isotropic materials IV. Further developments of the general theory. Philos Trans R Soc London Ser A Math Phys Sci 241(835):379\u2013397. https:\/\/doi.org\/10.1098\/rsta.1948.0024","journal-title":"Philos Trans R Soc London Ser A Math Phys Sci"},{"key":"1290_CR6","doi-asserted-by":"publisher","unstructured":"Gent AN, Thomas AG (1958) Forms for the stored (strain) energy function for vulcanized rubber. J Polym Sci 28(118):625\u2013628. https:\/\/doi.org\/10.1002\/pol.1958.1202811814","DOI":"10.1002\/pol.1958.1202811814"},{"issue":"1567","key":"1290_CR7","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1098\/rspa.1972.0026","volume":"326","author":"RW Ogden","year":"1972","unstructured":"Ogden RW (1972) Large deformation isotropic elasticity - on the correlation of theory and experiment for incompressible rubberlike solids. Proc R Soc London A Math Phys Sci 326(1567):565\u2013584. https:\/\/doi.org\/10.1098\/rspa.1972.0026","journal-title":"Proc R Soc London A Math Phys Sci"},{"key":"1290_CR8","doi-asserted-by":"crossref","unstructured":"Avril S, Bonnet M, Bretelle A-S, Gr\u00e9diac M, Hild F, Ienny P, Latourte F, Lemosse D, Pagano S, Pagnacco E, Pierron F (2008) Overview of identification methods of mechanical parameters based on full-field measurements. Exp Mech 48(4):381\u2013402","DOI":"10.1007\/s11340-008-9148-y"},{"key":"1290_CR9","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.ijsolstr.2018.11.008","volume":"184","author":"S Roux","year":"2020","unstructured":"Roux S, Hild F (2020) Optimal procedure for the identification of constitutive parameters from experimentally measured displacement fields. Int J Solids Struct 184:14\u201323. https:\/\/doi.org\/10.1016\/j.ijsolstr.2018.11.008","journal-title":"Int J Solids Struct"},{"key":"1290_CR10","doi-asserted-by":"crossref","unstructured":"Fuhg JN, Anantha Padmanabha G, Bouklas N, Bahmani B, Sun W, Vlassis NN, Flaschel M, Carrara P, De Lorenzis L (2024) A review on data-driven constitutive laws for solids. Arch Comput Methods Eng 1\u201343","DOI":"10.1007\/s11831-024-10196-2"},{"issue":"4","key":"1290_CR11","doi-asserted-by":"publisher","DOI":"10.1115\/1.4066118","volume":"77","author":"U R\u00f6mer","year":"2025","unstructured":"R\u00f6mer U, Hartmann S, Tr\u00f6ger J-A, Anton D, Wessels H, Flaschel M, De Lorenzis L (2025) Reduced and all-at-once approaches for model calibration and discovery in computational solid mechanics. Appl Mech Rev 77(4):040801. https:\/\/doi.org\/10.1115\/1.4066118","journal-title":"Appl Mech Rev"},{"key":"1290_CR12","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.cma.2016.02.001","volume":"304","author":"T Kirchdoerfer","year":"2016","unstructured":"Kirchdoerfer T, Ortiz M (2016) Data-driven computational mechanics. Comput Methods Appl Mech Eng 304:81\u2013101","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1290_CR13","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s00205-017-1214-0","volume":"229","author":"S Conti","year":"2018","unstructured":"Conti S, M\u00fcller S, Ortiz M (2018) Data-driven problems in elasticity. Arch Ration Mech Anal 229:79\u2013123","journal-title":"Arch Ration Mech Anal"},{"key":"1290_CR14","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.compstruc.2017.07.031","volume":"194","author":"LTK Nguyen","year":"2018","unstructured":"Nguyen LTK, Keip M-A (2018) A data-driven approach to nonlinear elasticity. Comput Struct 194:97\u2013115","journal-title":"Comput Struct"},{"key":"1290_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2020.113390","volume":"372","author":"P Carrara","year":"2020","unstructured":"Carrara P, De Lorenzis L, Stainier L, Ortiz M (2020) Data-driven fracture mechanics. Comput Methods Appl Mech Eng 372:113390","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1290_CR16","doi-asserted-by":"publisher","unstructured":"Huang DZ, Xu K, Farhat C, Darve E (2020) Learning constitutive relations from indirect observations using deep neural networks. J Comput Phys 416:109491. https:\/\/doi.org\/10.1016\/j.jcp.2020.109491, https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0021999120302655","DOI":"10.1016\/j.jcp.2020.109491"},{"issue":"1","key":"1290_CR17","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1038\/s41524-022-00884-7","volume":"8","author":"X Zhong","year":"2022","unstructured":"Zhong X, Gallagher B, Liu S, Kailkhura B, Hiszpanski A, Han TY-J (2022) Explainable machine learning in materials science. NPJ Comput Mater 8(1):204","journal-title":"NPJ Comput Mater"},{"key":"1290_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmps.2022.105076","volume":"169","author":"P Thakolkaran","year":"2022","unstructured":"Thakolkaran P, Joshi A, Zheng Y, Flaschel M, De Lorenzis L, Kumar S (2022) Nn-euclid: Deep-learning hyperelasticity without stress data. J Mech Phys Solids 169:105076","journal-title":"J Mech Phys Solids"},{"issue":"1","key":"1290_CR19","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1038\/s41524-023-01000-z","volume":"9","author":"P Xu","year":"2023","unstructured":"Xu P, Ji X, Li M, Lu W (2023) Small data machine learning in materials science. NPJ Comput Mater 9(1):42","journal-title":"NPJ Comput Mater"},{"key":"1290_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2021.113852","volume":"381","author":"M Flaschel","year":"2021","unstructured":"Flaschel M, Kumar S, De Lorenzis L (2021) Unsupervised discovery of interpretable hyperelastic constitutive laws. Comput Methods Appl Mech Eng 381:113852","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"1","key":"1290_CR21","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1038\/s41524-022-00752-4","volume":"8","author":"M Flaschel","year":"2022","unstructured":"Flaschel M, Kumar S, De Lorenzis L (2022) Discovering plasticity models without stress data. NPJ Comput Mater 8(1):91","journal-title":"NPJ Comput Mater"},{"key":"1290_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmat.2023.104643","volume":"181","author":"E Marino","year":"2023","unstructured":"Marino E, Flaschel M, Kumar S, De Lorenzis L (2023) Automated identification of linear viscoelastic constitutive laws with euclid. Mech Mater 181:104643","journal-title":"Mech Mater"},{"key":"1290_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2022.115867","volume":"405","author":"M Flaschel","year":"2023","unstructured":"Flaschel M, Kumar S, De Lorenzis L (2023) Automated discovery of generalized standard material models with euclid. Comput Methods Appl Mech Eng 405:115867","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1290_CR24","unstructured":"Flaschel M (2023) Automated discovery of material models in continuum solid mechanics, Ph.D. thesis, ETH Zurich"},{"key":"1290_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2022.115225","volume":"398","author":"A Joshi","year":"2022","unstructured":"Joshi A, Thakolkaran P, Zheng Y, Escande M, Flaschel M, De Lorenzis L, Kumar S (2022) Bayesian-euclid: Discovering hyperelastic material laws with uncertainties. Comput Methods Appl Mech Eng 398:115225","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1290_CR26","doi-asserted-by":"publisher","unstructured":"Kissas G, Mishra S, Chatzi E, De Lorenzis L (2024) The language of hyperelastic materials. Comput Methods Appl Mech Eng 428:117053. https:\/\/doi.org\/10.1016\/j.cma.2024.117053, https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0045782524003098","DOI":"10.1016\/j.cma.2024.117053"},{"key":"1290_CR27","doi-asserted-by":"publisher","unstructured":"Linka K, Kuhl E (2024) Best-in-class modeling: A novel strategy to discover constitutive models for soft matter systems. Extreme Mech Lett 70:102181. https:\/\/doi.org\/10.1016\/j.eml.2024.102181, https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2352431624000610","DOI":"10.1016\/j.eml.2024.102181"},{"key":"1290_CR28","doi-asserted-by":"crossref","unstructured":"Flaschel M, Hastie T, Kuhl E (2025) Non-smooth optimization meets automated material model discovery. arXiv:2507.10196","DOI":"10.1016\/j.jcp.2026.115043"},{"key":"1290_CR29","doi-asserted-by":"crossref","unstructured":"Urrea-Quintero J-H, Anton D, De Lorenzis L, Wessels H (2025) Automated constitutive model discovery by pairing sparse regression algorithms with model selection criteria","DOI":"10.1016\/j.cma.2025.118551"},{"key":"1290_CR30","doi-asserted-by":"crossref","unstructured":"Flaschel M, Yu H, Reiter N, Hinrichsen J, Budday S, Steinmann P, Kumar S, De Lorenzis L (2023) Automated discovery\u00a0of interpretable hyperelastic material models for human brain tissue with euclid. arXiv preprint arXiv:2305.16362","DOI":"10.1016\/j.jmps.2023.105404"},{"key":"1290_CR31","doi-asserted-by":"crossref","unstructured":"Holzapfel GA (2002) Nonlinear solid mechanics: a continuum approach for engineering science","DOI":"10.1023\/A:1020843529530"},{"issue":"44\u201345","key":"1290_CR32","doi-asserted-by":"publisher","first-page":"7999","DOI":"10.1016\/S0020-7683(01)00018-X","volume":"38","author":"S Hartmann","year":"2001","unstructured":"Hartmann S (2001) Parameter estimation of hyperelasticity relations of generalized polynomial-type with constraint conditions. Int J Solids Struct 38(44\u201345):7999\u20138018","journal-title":"Int J Solids Struct"},{"key":"1290_CR33","doi-asserted-by":"publisher","unstructured":"Tibshirani R (1996) Regression Shrinkage and Selection via the Lasso. J Roy Stat Soc: Ser B (Methodol) 58(1):267\u2013288. https:\/\/doi.org\/10.1111\/j.2517-6161.1996.tb02080.x","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"issue":"4","key":"1290_CR34","doi-asserted-by":"publisher","first-page":"813","DOI":"10.5254\/1.3546701","volume":"17","author":"LR Treloar","year":"1944","unstructured":"Treloar LR (1944) Stress-strain data for vulcanized rubber under various types of deformation. Rubber Chem Technol 17(4):813\u2013825","journal-title":"Rubber Chem Technol"},{"issue":"11","key":"1290_CR35","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1088\/0022-3727\/8\/11\/007","volume":"8","author":"D Jones","year":"1975","unstructured":"Jones D, Treloar L (1975) The properties of rubber in pure homogeneous strain. J Phys D Appl Phys 8(11):1285","journal-title":"J Phys D Appl Phys"},{"key":"1290_CR36","doi-asserted-by":"crossref","unstructured":"Brown R (2006) Physical testing of rubber, Springer Science & Business Media","DOI":"10.1007\/0-387-29012-5"},{"issue":"2","key":"1290_CR37","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1016\/j.polymertesting.2012.11.005","volume":"32","author":"D Moreira","year":"2013","unstructured":"Moreira D, Nunes L (2013) Comparison of simple and pure shear for an incompressible isotropic hyperelastic material under large deformation. Polym Testing 32(2):240\u2013248","journal-title":"Polym Testing"},{"key":"1290_CR38","unstructured":"GOM GmbH (2022) Aramis digital image correlation software. https:\/\/www.gom.com"},{"issue":"3","key":"1290_CR39","doi-asserted-by":"publisher","first-page":"504","DOI":"10.5254\/1.3547602","volume":"73","author":"MC Boyce","year":"2000","unstructured":"Boyce MC, Arruda EM (2000) Constitutive models of rubber elasticity: a review. Rubber Chem Technol 73(3):504\u2013523","journal-title":"Rubber Chem Technol"},{"issue":"9","key":"1290_CR40","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1007\/s00419-012-0610-z","volume":"82","author":"P Steinmann","year":"2012","unstructured":"Steinmann P, Hossain M, Possart G (2012) Hyperelastic models for rubber-like materials: consistent tangent operators and suitability for treloar\u2019s data. Arch Appl Mech 82(9):1183\u20131217","journal-title":"Arch Appl Mech"},{"key":"1290_CR41","doi-asserted-by":"crossref","unstructured":"Staverman A (1975) The gaussian chain in the theory of rubber elasticity. In: Journal of polymer science: polymer symposia, Vol. 51, Wiley Online Library, pp 45\u201356","DOI":"10.1002\/polc.5070510105"},{"key":"1290_CR42","unstructured":"Sutton MA, Orteu J-J, Schreier H (2009) Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications"},{"issue":"2","key":"1290_CR43","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1111\/str.12173","volume":"52","author":"Y Wang","year":"2016","unstructured":"Wang Y, Lava P, Reu P, Debruyne D (2016) Theoretical analysis on the measurement errors of local 2d dic: part i temporal and spatial uncertainty quantification of displacement measurements. Strain 52(2):110\u2013128","journal-title":"Strain"},{"key":"1290_CR44","doi-asserted-by":"publisher","unstructured":"Ghouli S, Flaschel M, Kumar S, De Lorenzis L (2025) A topology optimisation framework to design test specimens for one-shot identification or discovery of material models. J Mech Phys Solids 203:106210. https:\/\/doi.org\/10.1016\/j.jmps.2025.106210, https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0022509625001863, publisher: Elsevier BV","DOI":"10.1016\/j.jmps.2025.106210"},{"issue":"3\u20134","key":"1290_CR45","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1016\/j.ijsolstr.2008.09.025","volume":"46","author":"N Promma","year":"2009","unstructured":"Promma N, Raka B, Grediac M, Toussaint E, Le Cam J-B, Balandraud X, Hild F (2009) Application of the virtual fields method to mechanical characterization of elastomeric materials. Int J Solids Struct 46(3\u20134):698\u2013715","journal-title":"Int J Solids Struct"},{"issue":"7","key":"1290_CR46","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1016\/j.polymertesting.2009.06.001","volume":"28","author":"T Gu\u00e9lon","year":"2009","unstructured":"Gu\u00e9lon T, Toussaint E, Le Cam J-B, Promma N, Grediac M (2009) A new characterisation method for rubber. Polym Testing 28(7):715\u2013723","journal-title":"Polym Testing"},{"key":"1290_CR47","unstructured":"G\u2019Sell C, Coupard A (1996) G\u00e9nie M\u00e9canique des caoutchoucs et des \u00e9lastom\u00e8res thermoplastiques, Apollor"},{"key":"1290_CR48","doi-asserted-by":"crossref","unstructured":"Baaser H, Hopmann C, Schobel A (2013) Reformulation of strain invariants at incompressibility. Arch Appl Mech 83:273\u2013280","DOI":"10.1007\/s00419-012-0652-2"},{"key":"1290_CR49","unstructured":"Treloar LG (1975) The physics of rubber elasticity"}],"container-title":["Experimental Mechanics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11340-026-01290-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11340-026-01290-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11340-026-01290-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T19:22:05Z","timestamp":1791832925000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11340-026-01290-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,21]]},"references-count":49,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["1290"],"URL":"https:\/\/doi.org\/10.1007\/s11340-026-01290-6","relation":{},"ISSN":["0014-4851","1741-2765"],"issn-type":[{"value":"0014-4851","type":"print"},{"value":"1741-2765","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,21]]},"assertion":[{"value":"21 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2026","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This article was originally published under the subscription model but it is now published under an Open Access license.","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","label":"Ethical Approval","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent to Participate and Consent to Publish","group":{"name":"EthicsHeading","label":"Declarations"}},{"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","label":"Competing Interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}