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<jats:p>Integration of multiple data types is beneficial for prediction of geological characteristics. From the perspective that geochemistry characterizes the composition of a rock mass, hyperspectral data characterizes alteration mineralogy, and image feature extraction characterizes texture, most geological classifications would be well-informed by the combination of these three features. The process of meaningfully integrating distinctly sourced datasets and producing scale-relevant predictions for geological classifications involves several steps. We demonstrate a workflow to comprehensively structure and integrate these three feature families, refine training data, predict alteration classes, and mitigate noise derived from scale mismatch in output predictions. The dataset, compiled from the Josemaria porphyry copper deposit in Argentina, is comprised of more than 14,000 intervals of approximately 2 m, taken from 36 drillholes, where geochemistry was merged with hyperspectral mineralogy represented as tabular pixel abundances, and textural metrics extracted from core imagery, structured into the geochemical interval. Feature engineering and principal component analysis provided insights into the behavior of the ore system during intermediate steps, as well as providing uncorrelated feature inputs for a random forest predictor. Training data were refined by producing an initial prediction, thresholding the predictions to &gt;70% dominant class probability and using those (high probability) samples to produce a final model encoding better constrained separation between alteration assemblages. Prediction using the final model returned an accuracy of 82.5 %, as a function of model discrepancy combined with logging ambiguity and a scale mismatch between generalized logged intervals and much more granular (2 m) feature inputs. Noise reduction and generalization to desired resolution of output was achieved by applying the multiscale multivariate continuous wavelet transform tessellation method to class membership probabilities. Ultimately a large database of logged drill-core was homogenized using empirical methodologies. The described workflow is adaptable to distinct scenarios with some modification and is apt for integrating multiple input feature types and using them to systematically define geological classifications in drill-hole data.</jats:p>

<jats:p> In this study, we present summary statistics for multi-element soil geochemistry across Western Australia based on over 74,000 soil samples using the UltraFine+ <jats:sup>®</jats:sup> method that extracts and analyses the clay (&lt;2 µm) fraction of a soil sample. This method is a critical advancement for the detection of mobile element signatures for soil geochemical mineral exploration surveys in cover. However, existing estimates of background metal abundances acquired with other methods and on different sample media do not readily provide context for these analyses as recovery from the fine fraction differs to that of whole-sample analysis. We therefore present herein the geochemical results for 52 elements including precious, base and critical metals, as well as commonly associated pathfinder elements for Western Australian samples analysed during several research projects by the Commonwealth Scientific and Industrial Research Organisation. This dataset is separated by tectonic unit, into the Eastern Goldfields Superterrane and the Youanmi Terrane in the Yilgarn Craton, the Pilbara Craton and Sylvania Inlier, the Gascoyne, Lamboo and Aileron Provinces, and the Bryah and Earaheedy Basins to provide exploration-relevant context in these areas. We discuss some of the general trends observed for twelve of these elements, as well as some considerations for the use of these data in comparison to other geochemical soil surveys and with regards to mineral exploration settings. The samples presented in this study are not evenly distributed across Western Australia and limited information is available to correlate whether lithology at depth is mineralised or barren. However, in the absence of other, systematic datasets using the &lt;2 µm size fraction, these data present a suitable first-pass resource of element abundance ranges in areas of mineral exploration interest using the UltraFine+ <jats:sup>®</jats:sup> method in some of the mineral endowed areas of Western Australia. </jats:p> <jats:p content-type="supplementary-material"> <jats:bold>Supplementary material:</jats:bold> <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" specific-use="dataset is-supplemented-by" xlink:href="https://doi.org/10.6084/m9.figshare.c.6919933">https://doi.org/10.6084/m9.figshare.c.6919933</jats:ext-link> </jats:p>

<jats:p>Natural clay minerals, because of their physical and chemical characteristics are good adsorbents of metals. Among metals we often investigate heavy metals, but redox-sensitive metals are getting more and more attention. Redox-sensitive elements were measured in clay pit samples from clay mine in Bosnia and Herzegovina. For the purpose of analysis, a 23 m deep clay pit core sample was taken. From this sample 45 clay pit subsamples from different depths were used. The pH, electrical conductivity (EC), oxidation-reduction potential (ORP) and redox-sensitive elements content were measured. Amounts of redox-sensitive metals and aluminum were measured with an ICP-OES instrument. For statistical evaluation, maximum, minimum, average, median, correlation, correlation applying Al normalization and clr transformation were calculated. When justified PCA analysis was performed. The results are showing acidic pH, and oxidative ORP. The EC varied significantly through the sediment. The element concentrations lie in the sequence: Fe&gt;Ti&gt;V&gt;As. There is a significant change in correlations with and without Al-normalization. The highest difference in was found in case of titanium and vanadium (r value ranging from -0.553 to 0.835). Correlations and PCA after clr transformation showed mainly strong negative correlations, meaning that redox sensitive elements behave differently in clay samples.</jats:p> <jats:p content-type="supplementary-material"> <jats:bold>Supplementary material:</jats:bold> <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" specific-use="dataset is-supplemented-by" xlink:href="https://doi.org/10.6084/m9.figshare.c.7014329">https://doi.org/10.6084/m9.figshare.c.7014329</jats:ext-link> </jats:p>

<jats:p>The pollution risk of potentially toxic elements (PTEs) in soil is a common concern in the fields of environment science and agriculture. The spatial distribution characteristics, pollution risk assessment and genetic sources of PTEs in soil in high geological background areas are crucial to the safe use of land. Based on the data for five potentially toxic elements in 921 surface soil samples from typical geological high background areas in southwest China, we discuss their spatial distribution characteristics using geostatistics, semivariance function and its model, and carry out pollution risk assessment using the Integrated Impact Index of Quality (IICQ) and analyse their genetic sources using the Unmix receptor model. The spatial distribution of element content has a high spatial coupling with the stratigraphic spread, which is interfered by external random factors, resulting in a weakened autocorrelation. IICQ indicates soil is dominated by mild and moderate pollution, accounting for 42.24 % and 44.95 % respectively, with Cd contributing up to 63.00% to IICQ. Chromium and Cd are controlled by natural sources, accounting for 83.98 % and 69.39 % respectively. Arsenic and Hg have anthropogenic sources, accounting for 68.7 % and 44.0 %, respectively. Lead is controlled by both lead-zinc mining and geological background, accounting for 47.7% and 36.4% respectively. The Unmix model demonstrates that the spatial variability of PTEs is influenced by anthropogenic factors, such as coal combustion emissions, which account for 30.1% of the pollution sources. Soil parent material sources contribute 49.4%, followed by lead-zinc mining and smelting activities at 20.5%.</jats:p>

<jats:p>The Hormuz Island banded iron formations (HIBIFs) is situated at the Zagros Folded Zone in southern Iran. The BIFs occur intercalated with Neoproterozoic Hormuz series, an evaporite and siliciclastic succession with pyroclastic rocks, were deposited on the continental rift margin of the Arabian plate. The HIBIFs are banded rocks consisting of alternation of dark Fe-rich and reddish-brown Si-rich layers, and belong to oxide facies iron formations. The Post-Archean Australian Shale (PAAS)-normalized REY patterns of HIBIFs have the characteristics of both hydrothermal solutions and seawater. The sharp positive Eu anomaly (2.10–6.90) may be inherited from high-temperature hydrothermal solutions, while slightly negative Ce anomalies (0.57–0.82) is inherited from seawater. Homogenization temperature and salinity of primary fluid inclusions ranging from 180.7-474.3°C and from 2.24 to 12.85 wt% NaCl, respectively, which suggests the contribution of intermediate- to high-temperature hydrothermal fluids and seawater in forming of the HIBIFs. The Eu/Sm and Sm/Yb ratios in BIFs are between the values of hydrothermal fluids and seawater. In summary, all geological and geochemical data suggest that HIBIFs is the post-great oxidation event (GOE) iron formation pulse in the end Ediacaran period. However, it is actually not similar to Neoproterozoic syn-glacial iron formations. Instead, this is a new IF occurrence in an overlooked/understudied time period when either global or local conditions were conducive to iron deposition. The iron deposition in the Hormuz Island does not appear to be triggered by fluctuating atmospheric oxygen or sea-level variations, but instead may be related to syn-basinal volcanism in active continental rift margin environment in anoxic submarine condition.</jats:p> <jats:p content-type="thematic-collection"> <jats:bold>Thematic collection:</jats:bold> This article is part of the Geochemical processes related to mined, milled, or natural metal deposits collection available at: <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://www.lyellcollection.org/topic/collections/geochemical-processes-related-to-mined-milled-or-natural-metal-deposits">https://www.lyellcollection.org/topic/collections/geochemical-processes-related-to-mined-milled-or-natural-metal-deposits</jats:ext-link> </jats:p>

<jats:p> Ascertaining regional radiogeochemical characteristics and lithospheric thermal structure characteristics is paramount for identifying the resource potential of hot dry rocks (HDRs). This study conducted thermal conductivity testing and whole-rock analyses of outcrop granites of different formation epochs from the Tengchong area. Moreover, combined with the previously published whole-rock data and the data related to radioactive heat production rates, this study conducted geological, geophysical, and geothermal analyses. Key findings are as follows: (1) Granites in the Tengchong area exhibit an average radioactive heat generation rate of 5.54 μW/m <jats:sup>3</jats:sup> . Among them, the Late Cretaceous granites have an average radioactive heat generation rate of 8.08 μW/m <jats:sup>3</jats:sup> , suggesting high heat production granites; (2) Granites in the Tengchong area present an average thermal conductivity of 3.135 W/(m·K), relatively akin to the average values of granitic rocks worldwide. Compared to granites of other epochs, the Late Cretaceous granites manifest significantly higher thermal conductivities, with an average of 3.28 W/(m·K); (3) There is a negative correlation between the mica content and the thermal conductivity of the granites in the Tengchong area; (4)The Tengchong area holds potential for HDR exploitation and is inferred to have a lithospheric structure characterized by hot mantle and cold crust. </jats:p>