Estimation of the Mesozoic geological time scale

Geological time scales are constructed by combining the stratigraphic record with radiometric dates and their standard deviations. The stratigraphic record encompasses litho-, bio-, chrono-, and magnetostratigraphy. The statistical methods employed should embody concepts and data available for the systems considered. Recently, in order to estimate the ages of 31 Mesozoic stage boundaries, use was made of a database with chronostratigraphic classifications for 340 dates, biostratigraphic data including ammonite subzones, and information on seafloor spreading. This paper is primarily concerned with the propagation of errors through the successive steps of the data analysis. The following stepwise approach was taken for combining the different types of data: (1) maximum likelihood estimation with windows set around prior stage boundary estimates, (2) averaging of estimates with variable precision including magnetochronologic data, and (3) calibration by means of cubic smoothing splines assuming equal duration of ammonite subzones. The end product is a time-scale in which the stage boundary ages are accompanied by approximate 95 per cent confidence intervals.     

Conditional Independence Test for Weights-of-Evidence Modeling

Weights-of-evidence modeling is a GIS-based technique for relating a point pattern for locations of discrete events with several map layers. In general, the map layers are binary or ternary. Weights for presence, absence or missing data are added to a prior logit. Updating with two or more map layers is allowed only if the map layers are approximately conditionally independent of the point pattern. The final product is a map of posterior probabilities of occurrence of the discrete event within a small unit cell. This paper contains formal proof that conditional independence of map layers implies that T, the sum of the posterior probabilities weighted according to unit cell area, is equal to n, being the total number of discrete events. This result is used in the overall or omnibus test for conditional independence. In practical applications, T generally exceeds n, indicating a possible lack of conditional independence. Estimation of the standard deviation of T allows performance of a one-tailed test to check whether or not T-n is significantly greater than zero. This new test is exact and simpler to use than other tests including the Kolmogorov-Smirnov test and various chi-squared tests adapted from discrete multivariate statistics.     

The mineralogy and mineral associations of platinum group elements and gold in the Platreef at Zwartfontein, Akanani Project, Northern Bushveld Complex, South Africa

The mineralogy of the platinum-group elements (PGE), and gold, in the Platreef of the Bushveld Complex, was investigated using an FEI Mineral Liberation Analyser. Polished sections were prepared from 171 samples collected from two boreholes, for the in-situ examination of platinum group minerals (PGM). PGM and gold minerals encountered include maslovite (PtBiTe, 32 area% of total PGM), kotulskite (Pd(BiTe), 17?%), isoferroplatinum (Pt₃Fe, 15?%), sperrylite (PtAs₂, 11?%), cooperite (PtS, 5?%), moncheite (PtTe₂; 5?%), electrum (AuAg; 5?%), michenerite (PdBiTe; 3?%), Pd alloys (Pd, Sb, Sn; 3?%), hollingworthite ((Rh,Pt)AsS; 2?%), as well as minor (all <1 area% of total PGM) merenskyite (PdBiTe₂), laurite (RuS₂), rustenburgite (Pt_0.4Pd_0.4Sn_0.2), froodite (PdBi₂), atokite (Pd_0.5Pt_0.3Sn_0.2), stumpflite (PtSb), plumbopalladinite (Pd₃Pb₂), and zvyagintsevite (Pd₃Pb). An observed association of all PGM with base metal sulfides (BMS), and a pronounced association of PGE tellurides, arsenides and Pd&Pt alloys with secondary silicates, is consistent with the remobilisation and recrystallisation of some of the PGM’s during hydrothermal alteration and serpentinisation subsequent to their initial (primary) crystallisation from BMS (e.g. Godel et al. J Petrol 48:1569–1604, 2007; Hutchinson and McDonald Appl Earth Sci (Trans Inst Min Metall B) 114:B208–224, 2008).     

Evaluation of the uncertainty in estimation of metal resources of skarn tin in Southern China

This study is concerned with the problem of how many undiscovered mineral deposits can be expected to occur in the vicinity of any known deposit, especially if the deposit is nearly mined out. Skarn tin deposits in southern China were chosen to demonstrate that fractal modeling can be a useful tool to characterize the spatial–temporal distribution of mineral deposits, and to quantify their grades and tonnages. The results show that the spatial–temporal distribution of skarn tin deposits as well as their grades and tonnages satisfy fractal statistic, and suggest that 14 skarn tin deposits could be found around a known skarn tin deposit within a radius of 80 km. Monte Carlo simulation was used to combine the number of deposits and the frequency distributions of grade and tonnage and to capture the uncertainty in estimation of metal resources. At the 90%, 50% and 10% confidence levels, tin metal resources amount to 6 ton, 200 ton, and 1.0 × 10⁴ ton around a known tin deposit within a radius of 80, respectively.