Kuhl, 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

KUHL, Eileen, ZANG, Christian Siegfried, ESPER, Jan, RIECHELMANN, Dana, BÜNTGEN, Ulf, BRIESCH, Martin, REINIG, Frederick, RÖMER, Philipp, KONTER, Oliver, SCHMIDHALTER, Martin und HARTL, Claudia, 2023. Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers. Ecosphere. 2023. No. Band 14, Heft 3 (2023), Artikel-ID: e4453, p. , Heft 3 (2023), Artikel-ID: e4453. DOI 10.25358/openscience-9169.

Kuhl, 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.

Kuhl, Eileen/Zang, Christian Siegfried/Esper, Jan/Riechelmann, Dana/Büntgen, Ulf/Briesch, Martin u. a.: Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers, Ecosphere 2023, , Heft 3 (2023), Artikel-ID: e4453.

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, Wiley Ithaca, NY : ESA, 2010-, Weinheim, No. Band 14, Heft 3 (2023), Artikel-ID: e4453, S. , Heft 3 (2023), Artikel-ID: e4453.