Kuhl, E., Zang, C.S., Esper, J., Riechelmann, D., Büntgen, U., Briesch, M., Reinig, F., Römer, P., Konter, O., Schmidhalter, M. und Hartl, C. (2023) „Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers“, Ecosphere, (Band 14, Heft 3 (2023), Artikel-ID: e4453), S. , Heft 3 (2023), Artikel-ID: e4453. doi:10.25358/openscience-9169.
Chicago Manual of Style 17th edition (full note)Kuhl, Eileen, Christian Siegfried Zang, Jan Esper, Dana Riechelmann, Ulf Büntgen, Martin Briesch, Frederick Reinig, Philipp Römer, Oliver Konter, Martin Schmidhalter, und Claudia Hartl. „Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers“. Electronic. Ecosphere, Nr. Band 14, Heft 3 (2023), Artikel-ID: e4453 ([2023?]): , Heft 3 (2023), Artikel-ID: e4453. https://doi.org/10.25358/openscience-9169.
American Psychological Association 7th editionKuhl, E., Zang, C. S., Esper, J., Riechelmann, D., Büntgen, U., Briesch, M., Reinig, F., Römer, P., Konter, O., Schmidhalter, M., & Hartl, C. (ca. 2023). Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers [Electronic]. Ecosphere, Band 14, Heft 3 (2023), Artikel-ID: e4453, , Heft 3 (2023), Artikel-ID: e4453. https://doi.org/10.25358/openscience-9169
Modern Language Association 9th editionKuhl, E., C. S. Zang, J. Esper, D. Riechelmann, U. Büntgen, M. Briesch, F. Reinig, P. Römer, O. Konter, M. Schmidhalter, und C. Hartl. „Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers“. Ecosphere, electronic, Nr. Band 14, Heft 3 (2023), Artikel-ID: e4453, Wiley Ithaca, NY : ESA, 2010-, 2023, S. , Heft 3 (2023), Artikel-ID: e4453, https://doi.org/10.25358/openscience-9169.
ISO-690 (author-date, Deutsch)KUHL, Eileen, Christian Siegfried ZANG, Jan ESPER, Dana RIECHELMANN, Ulf BÜNTGEN, Martin BRIESCH, Frederick REINIG, Philipp RÖMER, Oliver KONTER, Martin SCHMIDHALTER und Claudia HARTL, 2023. Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers. Ecosphere. 2023. Nr. Band 14, Heft 3 (2023), Artikel-ID: e4453, S. , Heft 3 (2023), Artikel-ID: e4453. DOI 10.25358/openscience-9169