REMOBILIZED GEOCHEMICAL ANOMALIES RELATED TO DEEP GOLD ZONES, CARLIN TREND, NEVADA

J. K. Cluer

doi:10.2113/econgeo.107.7.1343

REMOBILIZED GEOCHEMICAL ANOMALIES RELATED TO DEEP GOLD ZONES, CARLIN TREND, NEVADA

Economic Geology ◽

10.2113/econgeo.107.7.1343 ◽

2012 ◽

Vol 107 (7) ◽

pp. 1343-1349 ◽

Cited By ~ 1

Author(s):

J. K. Cluer

Keyword(s):

Geochemical Anomalies ◽

Carlin Trend

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Map and interpretation of geochemical anomalies in the White Mountains, Blanco Mountain, Birch Creek, and Black Canyon Roadless Areas, White Mountains, California and Nevada

10.3133/mf1361b ◽

1983 ◽

Keyword(s):

Mountain Birch ◽

White Mountains ◽

Geochemical Anomalies ◽

Roadless Areas

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Deep electrical geophysical measurements across the Carlin Trend, Nevada

Open-File Report ◽

10.3133/ofr00419 ◽

2000 ◽

Author(s):

Jackie M. Williams ◽

Brian D. Rodriguez

Keyword(s):

Carlin Trend ◽

Geophysical Measurements

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Map showing barium, silver, and arsenic stream-sediment geochemical anomalies, Ambler River quadrangle, Alaska

Open-File Report ◽

10.3133/ofr78120g ◽

1979 ◽

Author(s):

Inyo F. Ellersieck

Keyword(s):

Stream Sediment ◽

Geochemical Anomalies

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Silver, copper, lead, and zinc stream-sediment geochemical anomalies in Misheguk Mountain Quadrangle, Alaska

Open-File Report ◽

10.3133/ofr80315 ◽

1980 ◽

Author(s):

S.M. Curtis ◽

I.F. Ellersieck ◽

C.F. Mayfield ◽

I.L. Tailleur

Keyword(s):

Stream Sediment ◽

Geochemical Anomalies ◽

Silver Copper ◽

Lead And Zinc ◽

Copper Lead

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Identification of geochemical anomalies using principal component analysis and factorial kriging analysis

Journal of Geochemical Exploration ◽

10.1016/0375-6742(93)90024-g ◽

1993 ◽

Vol 46 (3) ◽

pp. 245-256 ◽

Cited By ~ 20

Author(s):

R. Jimenez-Espinosa ◽

A.J. Sousa ◽

M. Chica-Olmo

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Factorial Kriging Analysis ◽

Geochemical Anomalies ◽

Factorial Kriging ◽

Kriging Analysis

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Big Data Analytics of Identifying Geochemical Anomalies Supported by Machine Learning Methods

Natural Resources Research ◽

10.1007/s11053-017-9357-0 ◽

2017 ◽

Vol 27 (1) ◽

pp. 5-13 ◽

Cited By ~ 37

Author(s):

Renguang Zuo ◽

Yihui Xiong

Keyword(s):

Machine Learning ◽

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Learning Methods ◽

Machine Learning Methods ◽

Geochemical Anomalies

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Geochemical anomalies from a survey of stream sediments in the Maquelab Area (Oecussi, Timor-Leste) and their bearing on the identification of mafic-ultramafic chromite rich complex

Applied Geochemistry ◽

10.1016/j.apgeochem.2020.104868 ◽

2020 ◽

pp. 104868

Author(s):

Victor A.S. Vicente ◽

João A.M. S. Pratas ◽

Frederico C.M. Santos ◽

Maria M.V. G. Silva ◽

Paulo J.C. Favas ◽

...

Keyword(s):

Stream Sediments ◽

Geochemical Anomalies ◽

Timor Leste

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Identifying geochemical anomalies and spatial distribution of gold and associated elements in the Zuru Schist Belt, northwest Nigeria

Arabian Journal of Geosciences ◽

10.1007/s12517-021-06828-7 ◽

2021 ◽

Vol 14 (6) ◽

Author(s):

Babatunde Joseph Fagbohun ◽

Oluseyi Adunola Bamisaiye ◽

Femi Joshua Ayoola ◽

Ayotunde Allen Omitogun ◽

Blessing Adeoti

Keyword(s):

Spatial Distribution ◽

Schist Belt ◽

Geochemical Anomalies

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Multivariate analysis of dilution-corrected residuals to improve the interpretation of geochemical anomalies and determine their potential sources: The Mingardo River case study (Southern Italy)

Journal of Geochemical Exploration ◽

10.1016/j.gexplo.2021.106890 ◽

2021 ◽

pp. 106890

Author(s):

Salvatore Dominech ◽

Shouye Yang ◽

Antonio Aruta ◽

Andrea Gramazio ◽

Stefano Albanese

Keyword(s):

Multivariate Analysis ◽

Southern Italy ◽

Geochemical Anomalies ◽

Potential Sources

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How double volcanic chains sample geochemical anomalies from the lowermost mantle

Earth and Planetary Science Letters ◽

10.1016/j.epsl.2012.09.057 ◽

2012 ◽

Vol 359-360 ◽

pp. 240-247 ◽

Cited By ~ 41

Author(s):

Cinzia G. Farnetani ◽

Albrecht W. Hofmann ◽

Cornelia Class

Keyword(s):

Geochemical Anomalies ◽

Lowermost Mantle

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