2017
DOI: 10.1016/j.lithos.2017.08.001
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Geochemical differentiation processes for arc magma of the Sengan volcanic cluster, Northeastern Japan, constrained from principal component analysis

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Cited by 32 publications
(22 citation statements)
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“…The reference slope for discrimination of tholeiitic (TH) and calc‐alkaline (CA) series is from Miyashiro (). The reference data for Quaternary volcanic rocks from NE‐Japan arc are summarized in Table S37 (Ban & Yamamoto, ; Fujinawa, , ; Hunter & Blake, ; Kimura & Yoshida, ; Kimura et al, ; Kudo et al, ; Kuritani, Yoshida, Kimura, Hirahara, et al, ; Moriguti et al, ; Ohba et al, ; Sakuyama & Nesbitt, ; Takahashi et al, ; Tatsumi et al, ; Toya et al, ; Ueki & Iwamori, ; Yamamoto, ).…”
Section: Resultsmentioning
confidence: 99%
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“…The reference slope for discrimination of tholeiitic (TH) and calc‐alkaline (CA) series is from Miyashiro (). The reference data for Quaternary volcanic rocks from NE‐Japan arc are summarized in Table S37 (Ban & Yamamoto, ; Fujinawa, , ; Hunter & Blake, ; Kimura & Yoshida, ; Kimura et al, ; Kudo et al, ; Kuritani, Yoshida, Kimura, Hirahara, et al, ; Moriguti et al, ; Ohba et al, ; Sakuyama & Nesbitt, ; Takahashi et al, ; Tatsumi et al, ; Toya et al, ; Ueki & Iwamori, ; Yamamoto, ).…”
Section: Resultsmentioning
confidence: 99%
“…Covariations between (a) SiO 2 and Sr, (b) SiO 2 and Y, (c) Mg# [≡Mg/(Mg + Fe 2+ )] and Sr/Y, and (d) Mg# and (La/Yb) n for the volcanic rocks in the Chugoku district. Data for NE‐Japan Quaternary lavas (fore‐arc volcanoes) are summarized in Tables S35–S37 (Ban & Yamamoto, ; Hunter & Blake, ; Kimura et al, ; Kimura & Yoshida, ; Kudo et al, ; Kuritani, Yoshida, Kimura, Hirahara, et al, ; Kuritani, Yoshida, Kimura, Takahashi, et al, ; Moriguti et al, ; Ohba et al, ; Sakuyama & Nesbitt, ; Takahashi et al, ; Tatsumi et al, ; Toya et al, ; Ueki & Iwamori, ).…”
Section: Resultsmentioning
confidence: 99%
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“…., in which PC1 explains the maximum variability, PC2 is the next major axis, and so on. Because PCA allows us to examine the factors contributing to the variance in the multidimensional data, an increasing number of studies have applied it to high-dimensional geochemical data of volcanic rocks, and successfully resolved the causes of geochemical variations resulting from the heterogeneity of primary magmas and/or magmatic differentiation (e.g., Bosch et al, 2008;Kuritani et al, 2016;Ueki and Iwamori, 2017).…”
Section: Principal Component Analysis On Basaltic Productsmentioning
confidence: 99%
“…Multivariate statistical analysis can be a powerful tool for detecting the characteristic features of multidimensional geochemical datasets, and it is employed in areas of study including environmental sciences, petrolo-gy, and resource exploration (e.g., Templ et al, 2008;Kuwatani et al, 2014;Ofner et al, 2015;Yasukawa et al, 2016;Ueki and Iwamori, 2017;Kuwatani et al, 2018;Ueki et al, 2018;Yoshida et al, 2018). Geochemical data including chemical composition, petrographic description, and location coordinates are increasingly provided in the literature, making them available for analysis approaches that deal with large-scale, multidimensional data (Igarashi et al, 2016).…”
Section: Introductionmentioning
confidence: 99%