This web form allows upload of zircon trace element data to a machine learning classifier which will attempt to predict a zircon grain’s primary host igneous lithology or ore deposit type. This website is designed to assist researchers classify zircon grains disassociated from their host rock.

Read me:

⦁ Select classification model (igneous rocks or ore deposits) and upload data file (.xlsx) of zircon trace element chemistry.

⦁ Data file must contain the following headers: Hf(ppm), Th(ppm), U(ppm), Ti(ppm), Nb(ppm), Ta(ppm), Eu(ppm), Lu(ppm) for igneous classification or Y(ppm), Eu(ppm), Hf(ppm), U(ppm), Ce(ppm), Ti(ppm), Th(ppm), Lu(ppm) for ore deposits. Note no space between element and unit in brackets. Each sample should be on its own row in the input file.

⦁ For igneous rocks, the Sheet name in the uploaded .xlsx file should be “Igneous Rocks Database”; if it is ore deposits, the Sheet name is “Ore Deposits Database”.

⦁ The output will provide classification predictions directly in the web page and also provide an option to download a more detailed classification result (.xlsx file).

⦁ There are some abbreviations in the prediction results: AR - acid rocks; IR - intermediate rocks; BR - basic rocks.

⦁ The detailed download result contains your uploaded zircon chemical data and predicted result for each zircon.

⦁ Uploaded data must contain at least ten zircon samples, otherwise an error will be reported.

AFTER CLASSIFICATION NO DATA IS STORED IN THE SYSTEM.

As you may imagine, we have invested hours of our time into this free project. Do you want to support us somehow? We would appreciate it if you quote the paper concerned with the classifier: p>

Reference:

Zi-Hao Wen, Lin Li, Christopher Kirkland, Sheng-Rong Li, Xiao-Jie Sun, Jia-Li Lei, Bo Xu & Zeng-Qian Hou. (2023). A Machine Learning Approach to Discrimination of Igneous Rocks and Ore Deposits by Zircon Trace Elements. American Mineralogist. DOI: 10.2138/am-2022-8899

Send us a message:

zihao_wen@126.com

Disclaimer:

While every effort is made to ensure the accuracy and completeness of the information provided through this classifier, the authors give no guarantee, assume no liability, nor take responsibility for the completeness, accuracy, or usefulness of the information produced by the classifier. Users should refer to other sources of geological information as well, especially when making commercial decisions.