A compiled experimental dataset of clinopyroxene-liquid pairs (2021-2025) for evaluating machine learning-based clinopyroxene

Creator(s):
Guo, Jie; ORCID: 0009-0007-4447-6296
Haozheng, Wang; ORCID: 0000-0002-6154-9561
Abstract:
This dataset is updated supplementary material for research article titled "Evaluation of Machine Learning-based Clinopyroxene Thermobarometers", including code and tables. Code: Python code for calculating the Mahalanobis distance and threshold. Table: 1. Table S1 Evaluation Dataset. 2. Table S2 Calculated Mahalanobis Distances: Table S2–1 Calculated Mahalanobis distances between each analysis in the evaluation dataset and the applicability domains of ML-based Cpx-only thermobarometers; Table S2–2 Calculated Mahalanobis distances between each analysis in the evaluation dataset and applicability domains of ML-based Cpx-Liq thermobarometers. 3. Table S3 Predicted Pressure and Temperature: Table S3–1 Predicted temperatures and pressures within applicability domains of ML-based Cpx thermobarometers; Table S3–2 Predicted temperatures and pressures outside applicability domains of ML-based Cpx thermobarometers; Table S3–3 Calculated temperatures and pressures by the Eq33&NP17 iterative thermobarometer; Table S3–4 Predicted pressures of diverse clinopyroxenes from Haoti Cenozoic melilitites. 4. Table S4 Recommendation result of ML-based Cpx thermobarometer selecting framework for diverse clinopyroxenes from Haoti Cenozoic melilitites.
How to cite this dataset:
Guo, J., Haozheng, W., 2026. A compiled experimental dataset of clinopyroxene-liquid pairs (2021-2025) for evaluating machine learning-based clinopyroxene, Version 1.0. Interdisciplinary Earth Data Alliance (IEDA). https://doi.org/10.60520/IEDA/114343. Accessed 2026-07-14.
DOI Creation Date:
2026-07-07
Related
Publication(s):
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Borghini, G., Fumagalli, P. & Rampone, E. (2022). Melt–rock interactions in a veined mantle: pyroxenite–peridotite reaction experiments at 2 GPa. European Journal of Mineralogy 34, 109-129. 10.5194/ejm-34-109-2022

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Fairchild, M. (2023). EXPERIMENTAL DETERMINATION OF LITHIUM PARTITIONING BETWEEN CLINOPYROXENE AND MELT. Cornell University.

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Ma, S. & Shaw, C. S. J. (2021). An Experimental Study of Trace Element Partitioning between Peridotite Minerals and Alkaline Basaltic Melts at 1250°C and 1 GPa: Crystal and Melt Composition Impacts on Partition Coefficients. Journal of Petrology 62. https://doi.org/10.1093/petrology/egab084

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Mouser, M. D. & Dygert, N. (2025). An experimental study of clinopyroxene- and garnet-melt trace element partitioning in Fe-rich basaltic systems. Advances in Geochemistry and Cosmochemistry 1, 719. https://doi.org/10.33063/agc.v1i2.719

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Shepherd, K., Namur, O., Toplis, M. J., Devidal, J.-L. & Charlier, B. (2022). Trace element partitioning between clinopyroxene, magnetite, ilmenite and ferrobasaltic to dacitic magmas: an experimental study on the role of oxygen fugacity and melt composition. Contributions to Mineralogy and Petrology 177, 90. https://doi.org/10.1007/s00410-022-01957-y
License:
Creative Commons Attribution 4.0 International [CC-BY-4.0]
Funding source(s):
National Natural Science Foundation of China: 42072225
National Research Foundation of Korea: RS–2024–00442775
Sichuan Provincial Creativity Training program: S202410615124
Southwest Petroleum University’s Research Program: 2023KSZ02016
Keyword(s):
Coverage Scope: Other
User Contributed Keyword(s):
Clinopyroxene; Thermobarometer; Machine Learning; Evaluation; Mahalanobis distance
Data Available On:
2026-07-09
Resource Type:
Collection
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4343-1_TableS1EvaluationDataset.xlsx
130.57 KB
4343-2_TableS2CalculatedMahalobisDistances.xlsx
72.63 KB
4343-3_TableS3PredictedPressureandTemperature.xlsx
137.39 KB
4343-4_TableS4Recommendation_Result.xlsx
21.98 KB
4343-5_ReadMe.docx
28.85 KB
4343-6_Code.zip
3.55 MB
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