摘要: Wildcat modelling of mineral prospectivity has been proposed for greenfields geologically-permissive terranes where targets have not yet discovered but a geological map is available as source spatial data predictors prospectivity. This paper (i) revisits the initial way assigning wildcat scores (Sc) to and (ii) proposes an improvement by transforming Sc into improved (ISc) using logistic function. was shown in low-sulphidation epithermal-Au (LSEG) deposits Aroroy district (Philippines). Based on knowledge characteristics controls LSEG mineralization Philippines, used study are proximity porphyry plutonic stocks, faults/fractures fault/fracture intersections. The ISc input separately principal components analysis extract favourability function that can be interpreted model predictive capacity based roughly 70% higher than predictors. A slight increase also achieved when integrated with geochemical anomalies, anomalies. significant because if were exploration area, then old methodology would caused several missed.
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