U–Pb geochronology of tin deposits associated with the Cornubian Batholith of southwest England: Direct dating of cassiterite by in situ LA-ICPMS

Moscati, Richard J.; Neymark, Leonid A.

doi:10.1007/s00126-019-00870-y

Cited by 48 publications

(27 citation statements)

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“…It was assumed that W was leached from an early W-bearing rutile, only to be deposited later in quartz veins as wolframite. Cassiterite, a mineral with the rutile structure, was also found to be enriched in tungsten and other elements (Wille et al 2018, Moscati andNeymark 2020;Bennett et al 2020). The proposed substitutions mechanisms in many of these studies, although feasible from a point of view of crystal chemistry, are rarely supported by data other than electron microprobe analyses.…”

Section: Discussionmentioning

confidence: 99%

“…Rutile and cassiterite are common minerals in many types of ore deposits, for example, greisen-type deposits (e.g., Moscati and Neymark 2020). Their trace element and isotopic composition carries much information about the ore-forming processes, and, therefore, cassiterite has been called the 'zircon of hydrothermal systems' (Blevin and Norman 2010), although this term could be equally well applied to rutile.…”

Section: Introductionmentioning

confidence: 99%

“…An element that is increasingly reported in elevated concentrations in rutile or cassiterite is tungsten (e.g., Kwak 1983, Rice et al 1998, Clark and Williams-Jones 2004, Müller and Halls 2005, Mozola et al 2017Reznitsky et al 2017;Moscati and Neymark 2020;Bennett et al 2020). The ore deposits of tungsten are commonly linked to acidic or intermediate igneous complexes but not all such complexes, no matter how evolved, develop an ore deposit, a camp of ore deposits, or even small ore occurrences (cf.…”

Section: Introductionmentioning

confidence: 99%

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Incorporation mechanism of tungsten in W-Fe-Cr-V-bearing rutile

Majzlan

Bolanz

Göttlicher

et al. 2021

American Mineralogist

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Rutile is a common mineral in many types of ore deposits and can carry chemical or isotopic information about the ore formation. For closer understanding of this information, the mechanisms of incorporation of minor elements should be known. In this work, we have investigated natural rutile crystals with elevated concentration of WO 3 (up to 17.7 wt.%), Cr 2 O 3,tot (7.5), V 2 O 3,tot (4.1), FeO tot (7.3), and other metals. X-ray absorption spectroscopy (XAS) on rutile on the Fe K, Cr K, V K, and W L 1 and L 3 edges shows that all cations are coordinated octahedrally. The average oxidation state of V is +3.8, that of Cr near +4. Shell-by-shell fitting of the W L 3 EXAFS data show that W resides in the rutile structure. Raman spectroscopy excluded the possibility of hydrogen as a chargecompensating species. High-resolution TEM and electron diffraction confirm this conclusion as the entire inspected area consists of rutile single crystal with variable amount of metals other than Ti. Our results show that rutile or its precursors can be efficient vehicles for tungsten in sedimentary rocks, leading to their enrichment in W and possibly later fertility This is the peer-reviewed, final accepted version for American Mineralogist, published by the Mineralogical Society of America. The published version is subject to change. Cite as Authors (Year) Title. American Mineralogist, in press.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Incorporation mechanism of tungsten in W-Fe-Cr-V-bearing rutile

Majzlan

Bolanz

Göttlicher

et al. 2021

American Mineralogist

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“…The association between granite type and mineral prospectivity is not wellconstrained; granite types close to surface are sometimes older than, and unrelated to, the mineralisation they host, e.g. Carnmenellis Granite (Moscati and Neymark, 2020).…”

Section: Permian Granite Batholithmentioning

confidence: 99%

“…These magmatic-hydrothermal systems are Early Permian in age and synchronous with batholith construction, based on Ar-Ar dating of muscovite wallrock alteration and U-Pb dating of cassiterite (Chen et al 1993;Chesley et al, 1993;Moscati and Neymark, 2020;Tapster and Bright, 2020). Fluid inclusion studies, on vein quartz and cogenetic wolframitecassiterite, indicate typical magmatic-hydrothermal fluids temperatures in the range 300-400°C (Jackson et al, 1977(Jackson et al, , 1989Campbell and Panter, 1990;Smith et al, 1996).…”

Section: Tungsten Mineralisation and Explorationmentioning

confidence: 99%

A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence

Yeomans¹,

Shail²,

Grebby³

et al. 2019

Preprint

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Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to a data-driven machine learning approach for tungsten mineralisation. The method emphasises the importance of appropriate model evaluation and develops a new Confidence Metric to generate spatially refined and robust exploration targets. The data-driven Random Forest™ algorithm is employed to model tungsten mineralisation in SW England using a range of geological, geochemical and geophysical evidence layers which include a depth to granite evidence layer. Two models are presented, one using standardised input variables and a second that implements fuzzy set theory as part of an augmented feature extraction step. The use of fuzzy data transformations mean feature extraction can incorporate some user-knowledge about the mineralisation into the model. The typically subjective approach is guided using the Receiver Operating Characteristics (ROC) curve tool where transformed data are compared to known training samples. The modelling is conducted using 34 known true positive samples with 10 sets of randomly generated true negative samples to test the random effect on the model. The two models have similar accuracy but show different spatial distributions when identifying highly prospective targets. Areal analysis shows that the fuzzy-transformed model is a better discriminator and highlights three areas of high prospectivity that were not previously known. The Confidence Metric, derived from model variance, is employed to further evaluate the models. The new metric is useful for refining exploration targets and highlighting the most robust areas for follow-up investigation. The fuzzy-transformed model is shown to contain larger areas of high model confidence compared to the model using standardised variables. Finally, legacy mining data, from drilling reports and mine descriptions, is used to further validate the fuzzy-transformed model and gauge the depth of potential deposits. Descriptions of mineralisation corroborate that the targets generated in these models could be undercover at depths of less than 300 m. In summary, the modelling workflow presented herein provides a novel integration of knowledge-driven feature extraction with data-driven machine learning modelling, while the newly derived Confidence Metric generates reliable mineral exploration targets.

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The Cornubian Batholith

SHAIL,

SIMONS

2023

Metallic Resources 1

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U–Pb geochronology of tin deposits associated with the Cornubian Batholith of southwest England: Direct dating of cassiterite by in situ LA-ICPMS

Cited by 48 publications

References 47 publications

Incorporation mechanism of tungsten in W-Fe-Cr-V-bearing rutile

Incorporation mechanism of tungsten in W-Fe-Cr-V-bearing rutile

A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence

The Cornubian Batholith

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