Journal of Geochemical Exploration最新文献

{"title":"Geochemistry and U-Pb dating of the Yahyalı pluton and associated skarn occurrences, SW Kayseri (Central Türkiye): Geodynamic significance and relation to mineralization","authors":"Fatma Şişman Tükel ,&nbsp;Deniz Tiringa ,&nbsp;Nurullah Hanilçi ,&nbsp;Bülent Ateşçi ,&nbsp;Namık Aysal ,&nbsp;İsmet Alan","doi":"10.1016/j.gexplo.2025.107756","DOIUrl":"10.1016/j.gexplo.2025.107756","url":null,"abstract":"<div><div>The Yahyalı Pluton is an intrusion that intruded into the Yahyalı Nappe in the Eastern Taurus Belt. However, its outcrops are observed in a narrow area due to insufficient erosion depth and few studies have been carried out. This pluton is mainly composed of granite, granodiorite, diorite and monzonite. These facies are predominantly calc-alkaline and partly high-K calc-alkaline series, with an I-type character. The geochemical behaviour of the pluton suggests that mafic magmas of mantle origin have undergone a high degree of fractional crystallization (FC) and may have been partially mixed and/or contaminated by felsic magmas of crustal origin.</div><div>In this study, the Yahyalı pluton and associated garnet skarn formations were dated for the first time. Zircon U-Pb dating of samples taken from different levels of the Yahyalı pluton yielded concordia ages of 52.37 ± 0.41 Ma, 53.66 ± 0.30 Ma, 52.59 ± 0.37 Ma and 52.05 ± 0.36 Ma, respectively. In addition, a lower intercept age of 50.1 ± 3.3 Ma (MSWD = 1.4) (Early Eocene) was obtained from garnet skarn formations. Although the pluton has limited outcrops, associated mineralization (Fe and Fe-Cu skarn, Pb-Zn) occurs over an extensive area, suggesting that large parts of the pluton may not have been eroded. This suggests that the Yahyalı pluton is a fertile magma in terms of mineralization and that there is a high potential for skarn, hydrothermal and porphyry-type mineralization associated with the magmatic system at deeper depths in the region.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"274 ","pages":"Article 107756"},"PeriodicalIF":3.4,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143703918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A semi-supervised learning framework for intelligent mineral prospectivity mapping: Incorporation of the CatBoost and Gaussian mixture model algorithms","authors":"Mahsa Hajihosseinlou ,&nbsp;Abbas Maghsoudi ,&nbsp;Reza Ghezelbash","doi":"10.1016/j.gexplo.2025.107755","DOIUrl":"10.1016/j.gexplo.2025.107755","url":null,"abstract":"<div><div>Semi-supervised learning warrants more significant consideration for machine learning-based mapping in mineral exploration, since mineral deposits frequently exhibit imbalances in occurrence frequencies. It can potentially address challenges associated with class imbalances via the efficient use of labeled data and the extrapolation of patterns from unlabeled data. This research endeavors to present a prospective model for Mississippi Valley-Type lead and zinc deposits employing a semi-supervised approach in the Varcheh district, western Iran. To achieve this goal, diverse exploratory criteria related to mineralization, encompassing geological, remote sensing, geochemical, and structural layers, have been incorporated to develop a semi-supervised mineral prospectivity model. The model strengthens the advantages of supervised and unsupervised learning approaches by incorporating the Categorical gradient Boosting (CatBoost) and Gaussian mixture model algorithms into a semi-supervised framework. This approach effectively utilizes limited labeled data, while capturing spatial patterns and relationships in the unlabeled dataset, ultimately contributing to a more robust mineral prospectivity mapping model. Indeed, the regions with high posterior probability include most lead and zinc deposits in this strategy, suggesting that the locations of known deposits are significantly tied to areas connected to high posterior probability. The semi-supervised proposed framework in this paper is also compared with supervised approach to validate the performance improvement. The implemented approach can be highly valuable for exploring resources.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"274 ","pages":"Article 107755"},"PeriodicalIF":3.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship between distribution of iodine in soil and iodine deficiency disorders (IDD) in China","authors":"Qingqing Liu ,&nbsp;Xueqiu Wang ,&nbsp;Daxing Zhai ,&nbsp;Bimin Zhang ,&nbsp;Lanshi Nie ,&nbsp;Qinghua Chi ,&nbsp;Jian Zhou ,&nbsp;Wei Wang ,&nbsp;Hanliang Liu ,&nbsp;Dongsheng Liu ,&nbsp;Yining Zhou ,&nbsp;Chan Chang","doi":"10.1016/j.gexplo.2025.107758","DOIUrl":"10.1016/j.gexplo.2025.107758","url":null,"abstract":"<div><div>Iodine deficiency disorder (IDD) is a serious public health issue in China. As iodine in the environment is the fundamental cause of iodine-endemic diseases, investigating the distribution and controlling factors of iodine in the soil of endemic disease areas for the accurate prevention and control of endemic diseases is important. This paper aimed to examine the concentration and spatial distribution of iodine in soil of China, along with its correlation with IDD, and explore the influence of geological background, soil types, and geomorphoclimatic landscapes. Based on the data of China Geochemical Baseline (CGB) project, China can be divided into seven high- and three low-value zones. We found that the formation of low-value zones is associated with the high mobility of iodine. According to the Specification of Land Quality Geochemical Assessment, I-deficient soil accounts for nearly 70 % of the land area in China. Meanwhile, the distribution of severe endemic diseases was more consistent with that of iodine concentration (&lt;0.654 mg/kg) in top samples. The high-value zones were closely related to biological affinity and adsorption of iodine, and were mainly distributed in areas with high organic carbon content and coastal areas. The distribution characteristics of iodine in soil and that of IDD were also linked to the geological background, soil types, and geomorphoclimatic landscapes. The predominant soil type in seriously endemic diseases areas was Argosols, and the predominant geomorphoclimatic landscapes was alpine canyons, accumulated Gobi desert, and karst regions. Apart from the karst terrain, other soil types and geomorphoclimatic landscapes mentioned above exhibited low-iodine concentrations.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"275 ","pages":"Article 107758"},"PeriodicalIF":3.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Driving factors of soil selenium accumulation in regional enrichment area at selenium-deficient soil belt of China: An enlightenment of Moran's index and machine learning","authors":"Yuanli Qin ,&nbsp;Li Zhang ,&nbsp;Qiaolin Wang ,&nbsp;Yuntao Song ,&nbsp;Min Peng ,&nbsp;Hangxin Cheng","doi":"10.1016/j.gexplo.2025.107746","DOIUrl":"10.1016/j.gexplo.2025.107746","url":null,"abstract":"<div><div>Selenium (Se) is one of the most indispensable trace elements for human beings, known as the ‘longevity element’ in the 21st century. Due to the complexity of the global geological environment, the distribution of soil Se varies significantly across the world. Understanding the distribution pattern and driving factors of soil Se enrichment is crucial for land resource development and addressing “hidden hunger”, especially in regions where soil Se is abundant. Therefore, a soil geochemical survey was conducted in the Baoshan area of southwest China, which is located at the Se-deficient soil belt yet exhibited characteristics of soil Se enrichment. Combined with Moran's I analysis and machine learning (ML), the enrichment and distribution characteristics, and driving factors of soil Se in this region were revealed. Specifically, we quantify the feature importance of each key factors. Additionally, distribution of soil Se demonstrated strong spatial dependence. The results from Bivariate Moran's I analysis, back-propagation artificial neural networks (BP–ANN) and random forest (RF) models indicated that soil organic carbon (SOC), pH, manganese (Mn), weathering eluvial index (ba), land use and parent materials are the primary driving factors of soil Se retention at the regional scale in Baoshan. In contrast, climate and topography, which are common factors affecting Se distribution at global and continental scales, were found to have no effect on Se retention at this regional scale. Based on the RF model, the relative importance of key driving factors are SOC (24.5 %), land use (21.1 %), pH (15.5 %), ba (15.2 %), parent materials (12.0 %), and Mn (11.9 %). These findings provide valuable guidance for agricultural managements planning and for adjusting agricultural planting structures in marginal and soil Se-rich regions of the traditional Se-deficient soil belt in China.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"274 ","pages":"Article 107746"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metallogenesis of the sediment-hosted copper deposits in the Miocene sandstones from Upper Red Formation, Zanjan, NW Iran","authors":"Ghasem Nabatian ,&nbsp;Mohammad Ebrahimi ,&nbsp;Osvaldo Rabbia","doi":"10.1016/j.gexplo.2025.107745","DOIUrl":"10.1016/j.gexplo.2025.107745","url":null,"abstract":"<div><div>The Chehrabad, Qezeljeh, and Sarikand copper deposits, located in the Zanjan district in northwestern Iran, are classified as sediment-hosted copper (SHC) deposit. These deposits mainly consist of fine-grained, disseminated base-metal sulfides cementing grey sandstones from the thick sequences of Miocene red beds (Upper Red Formation: URF). The ore-hosting grey sandstones contain carbonaceous materials (fossil plants) and fine-grained, disseminated framboidal pyrite. Copper, lead, zinc, and iron sulfides replace primary organic material as well as framboidal pyrite. Ore minerals such as chalcocite, galena, sphalerite, argentite, covellite, pyrite and minor chalcopyrite and bornite occur as replacement in organic matter and cement of the host sandstone. Geochemical analyses of the SHC deposits in the Zanjan district show an average of 5 wt% Cu, 6 wt% Pb and 3 wt% Zn, ~0.7 to 128 ppm for Ag, and ~ 0.1 to 821 ppm for Cd in the grey sandstone. This research aims to enhance the comprehension of the genesis of the SHC deposits in the Zanjan district, thereby providing direction for future exploration efforts in the area.</div><div>Electron probe micro-analysis (EPMA) was used to determine the mineral chemistry and occurrence of copper, lead, zinc, and silver in sulfide and carbonate minerals. The results reveal that argentite is associated with Cu-bearing minerals (mainly chalcocite and covellite). Furthermore, the presence of montetrisaite mineral, along with minor amounts of cadmium, has been identified. The studied samples from Zanjan SHC deposits show a range of δ³⁴S values from −1.90 ‰ to +12.9 ‰ values, indicating sulfur might have originated from framboidal pyrite, organic matter, evaporite layers, and salt diapirs of URF. The sulfide ore is vertically zoned, with Cu sulfides at lower stratigraphic levels and Pb-Zn-rich ore at the upper part. Ore-stage sulfide minerals were likely formed by the infiltration of ore-forming fluids originating from the underlying red beds into the grey sandstone layers during the Miocene, following the deposition of these rocks. The oxidized, low-temperature, metalliferous brine responsible for mineralization originated from highly porous and permeable sediments expelled during diagenetic events in the basin. Mineralization occurred within a favorable reducing environment, mainly provided by organic matter, framboidal pyrite, and reduction of the oxidized, low-temperature brine in the grey sandstone horizons. The timing of these deposits is typically late diagenetic. Concerning host rock lithology, mineral assemblages, fabric and structure of the ores, and the overall genetic interpretation, they are similar to the sediment-hosted stratiform copper deposits elsewhere such as Lisbon Valley (Utah, USA) and Nacimiento (New Mexico).</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"274 ","pages":"Article 107745"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of LUNAR, iForest, LOF, and LSCP methodologies in delineating geochemical anomalies for mineral exploration","authors":"Shahed Shahrestani ,&nbsp;Christian Conoscenti ,&nbsp;Emmanuel John M. Carranza","doi":"10.1016/j.gexplo.2025.107737","DOIUrl":"10.1016/j.gexplo.2025.107737","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Geochemical anomaly detection and delineation are crucial in mineral exploration, but they are challenged by high-dimensional data, complex inter-variable dependencies, and scarcity of ground truth labels for anomalies. Traditional outlier detection methods, including density-based and nearest-neighbor approaches, often misclassify anomalies close to the edges of the background data distribution, while ensemble methods face limitations in combining detectors effectively. Generic and global combination procedures frequently neglect local patterns in the data, leading to suboptimal detection of nuanced outlier characteristics, and the absence of robust selection processes can compromise ensemble performance due to underperforming detectors. To address these issues, this paper presents LUNAR (learnable unified neighborhood-based anomaly ranking), a novel outlier detection method that integrates graph neural networks with nearest neighbor analysis, and LSCP (locally selective combination in parallel outlier ensembles), which emphasizes local data structures and leverages pseudo-ground truth to optimize detector selection and improve score stability. This study also explored the efficacy of outlier detection methods, namely local outlier factor (LOF) and isolation forest (iForest) in detecting geochemical anomalies within the Varzaghan area, situated in the Ahar–Arasbaran zone of the Alborz–Azerbaijan Magmatic Belt. This region hosts diverse mineral occurrences, including porphyry Cu&lt;img&gt;Mo deposits (e.g., Sungun), epithermal base metal veins (e.g., Zaylik), and Fe&lt;img&gt;Cu skarn deposits (e.g., Sungun and Anjerd). Compared to the LOF and iForest, for the analysis of a trace element geochemical dataset from 1067 stream sediment samples, the LUNAR exhibited the highest relative percentage of delineated deposits along with superior AUC (area under curve) from ROC (receiver operating characteristic) analysis for both mineral occurrences and mineralized samples. The LOF-detected outliers for elements like As, Sb, and Ti, whereas the iForest-detected outliers for Ti, Pb, and Co, and the LUNAR-detected outliers for Au and pathfinder elements like As, Bi, and Sb. Employing a graph neural network, the LUNAR efficiently captured intricate outlier relationships within the multivariate geochemical dataset, surpassing the LOF. Spatial analysis uncovered a correlation between LSCP variants and the LUNAR in detecting geochemical anomalies and their association with known deposits. Based on AUC values, the LSCP_A (average) demonstrated relative superiority over the LSCP_AOM (average of maximum), LSCP_MOA (maximum of average), and LUNAR. Among the LSCP variants, the LSCP_A showcased superior performance, leveraging average scores, and detecting outliers of pathfinder elements for gold like As and Bi, along with lithologically-influenced elements like Cr and Ti, and the significant role of Cu. The mapping of clr-transformed Bi data aligned closely with mineral","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"273 ","pages":"Article 107737"},"PeriodicalIF":3.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Silicon isotope behavior during silica diagenesis recorded by silica sinters in a geothermal system, Xizang, China","authors":"Wei Wang ,&nbsp;Shao-Yong Jiang ,&nbsp;Hai-Zhen Wei ,&nbsp;Wen Zhang","doi":"10.1016/j.gexplo.2025.107744","DOIUrl":"10.1016/j.gexplo.2025.107744","url":null,"abstract":"<div><div>Silica sinters formed in geothermal systems represent an ideal geochemical archive for studying silicon (Si) isotope (δ³⁰Si) behavior during early diagenesis. Understanding diagenetic processes, including the preservation of Si isotope compositions, is crucial in the matter of paleo-environmental reconstruction. We conducted an investigation in the Dagejia geothermal system located in Xizang, China. This study presents silica diagenetic sequences that span from active geothermal fluids, transitioning from modern and fresh (MF) opal-A to modern and fresh (MF) chalcedony at temperatures ranging from 70 °C to 85 °C and high alkalinity. During diagenesis, the Si isotope values of chalcedony exhibit significant centimeter-scale variations, ranging from −1.89 ‰ to −0.35 ‰. From the top layer MF opal-A to the bottom layer MF chalcedony, the δ³⁰Si values decrease, and the Δ³⁰Si _{chalcedony-opal-A} increases from −1.65 ‰ at 70 °C to −1.05 ‰ at 85 °C.</div><div>In this process, the Si concentration of the pore fluid and the Si isotopic composition of the silica sinter were modeled via C.O model and Rayleigh model, respectively. The results show that the Si concentration of pore fluid is controlled by opal-A precursor dissolution and diagenetic depth. These variations in MF chalcedony are caused primarily by kinetic fractionation and are influenced by the temperature and Si concentration of the pore fluid. In this study, we demonstrate that silica diagenetic processes, coupled with isotopic changes in natural siliceous deposits, heavily depend on specific conditions during the formation of silica sinters. Furthermore, they may effectively preserve the initial information present after the formation of silica sinters. These interlinked controls on Si isotopic compositions are crucial for the application of Si isotopes in cherts for paleo-environmental reconstructions.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"273 ","pages":"Article 107744"},"PeriodicalIF":3.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geochemistry, geochronology and Fe-Mg-S isotopic composition of the Liaoshang gold deposit, Jiaodong Peninsula, China: Implications for ore-forming processes and mineral exploration","authors":"Yuan-lin Chen ,&nbsp;Huan Li ,&nbsp;Shang-yi Gu ,&nbsp;Scott A. Whattam ,&nbsp;Chao-yang Zheng ,&nbsp;Li-gong Wang ,&nbsp;Da-dou Li ,&nbsp;Liu-an Duan","doi":"10.1016/j.gexplo.2025.107738","DOIUrl":"10.1016/j.gexplo.2025.107738","url":null,"abstract":"<div><div>The Liaoshang Au deposit in North China is distinguished by gold occurrence in pyrite-dolomite veins and characterized by large Au endowment (about 69 t Au @ 3.3 g/t), representing a novel gold deposit type within the Jiaodong gold province. To date, the mineralization age and metallogenic mechanism remain controversial, limiting the in-depth understanding of ore-forming processes. The Liaoshang Au mineralization differs from classic orogenic Au metallogeny in close relationships with the occurrence of ore-stage pyrite and dolomite. Here, we use syn-ore stage monazite U-Pb geochronology to constrain the ore-forming age. We also measured Fe and Mg isotope compositions in pyrite and dolomite associated with gold mineralization, combined with in situ LA-(MC)-ICP-MS elemental mapping and S isotopes in pyrite to decipher the iron, magnesium, and sulfur source(s), aiming to provide new insights into the ore-forming processes. Petrographic observation shows that gold in pyrite-dolomite veins mainly occurs as micro-grains (20–100 μm) within pyrite. Elemental mapping and in situ S isotope measurements for pyrite indicate that the main Au mineralization is associated with elevated concentrations of Cu, Ag, As, and Bi, as well as heavy sulfur isotope values (δ³⁴S ~13.6 ‰, compared to ~8.0 ‰ in the early stage). This is attributed to the addition of sulfur with high δ³⁴S from the basement Jingshan Group. The δ⁵⁶Fe values of ankerite and pyrite present a narrow range with an average of −0.21 ‰ and +0.56 ‰, respectively. The inverse enrichment of iron isotopes between ankerite and pyrite may be attributed to thermodynamic equilibrium fractionation in an open system. The δ²⁶Mg values of ankerite yields a wide range from −3.02 ‰ to −0.80 ‰. By comparing the Fe and Mg isotopic signatures of ores with those of local granites and basement rocks, we argue that the Jingshan Group contributed Fe and Mg to form auriferous pyrite and dolomite. The U-Pb dating of monazite in Au-bearing pyrite yields an age of 118.8 ± 1.7 Ma, which may represent the mineralization age of the deposit. The ore-forming fluid sourced from metasomatized mantle lithosphere leached Fe, Mg, and some heavier sulfur from the Jingshan Group to precipitate pyrite and dolomite in Liaoshang, forming pyrite‑carbonate veins. This is a critical gold mineralization mechanism for forming the Liaoshang-type gold deposits in the Jiaodong Peninsula, North China, which is different from that of the Jiaojia-type (disseminated stockwork-altered wall-rock type) and Linglong-type (quartz-sulfide vein type) gold deposits.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"273 ","pages":"Article 107738"},"PeriodicalIF":3.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fluid and mineral inclusions of charoitite deposit in the Murun alkaline-carbonatite complex, Eastern Siberia, Russia","authors":"Emilia Yu. Dokuchits,&nbsp;Shao-Yong Jiang,&nbsp;Suo-Fei Xiong,&nbsp;Aleksandr Stepanov,&nbsp;Irina Zhukova,&nbsp;Wen-Tian Li","doi":"10.1016/j.gexplo.2025.107735","DOIUrl":"10.1016/j.gexplo.2025.107735","url":null,"abstract":"<div><div>The Murun alkaline‑carbonatite complex in Eastern Siberia, Russia, is known as a unique <em>gem</em> deposit of scenic purple charoitite rocks that consist of up to fifty different minerals, most of which are rare in nature. Charoitites occur in the rocks, which were identified as fenites. Rock-forming minerals of charoitites include charoite, pyroxene, K-feldspar, amphibole, and quartz; various (Ca)-(K)-(Na) silicates often present in large amounts. Apatite, carbonate minerals (mainly strontianite and barytocalcite), baryte, steacyite, dalyite, and various sulfides are typical accessory minerals in charoitites. Several transparent minerals from charoitites were studied in this paper, with special attention given to fluid and mineral inclusions. Fluid inclusions (FIs) are observed in quartz, apatite, tinaksite, dalyite, amphibole, pyroxene, and K-feldspar, including monophase [V (vapor) and L (liquid)], two-phase [L + V (liquid+vapor) and V + L (vapor+liquid)], multicomponent (L + V + S), and solid crystalline inclusions, which are represented by both single grain and composite mineral inclusions. The Raman spectra showed that most two-phase FIs are aqueous with minor N₂ and sometimes contain abundant CH₄ in the vapor phase. Using Raman spectroscopy, the daughter phases in multiphase inclusions were identified as sulfates (baryte and thenardite) and carbonates (witherite and calcite). The following crystalline phases in mineral inclusions were recorded: carbonates (witherite, calcite, barytocalcite, burbankite), sulfates (baryte), sulfides (sphalerite, galena and others), and silicates (quartz, aegirine, amphibole, and some Ca-(K)-(Na) silicate minerals). High-temperature polyphase melt inclusions were found in K-feldspar and tinaksite; however, only partial dissolution was achieved, and total homogenization could not be measured due to decrepitation. The studied fluid inclusions record a complex post-magmatic history, which includes the trapping of an aqueous fluid. The measured total homogenization temperatures (<em>T</em>_h) of FIs in quartz (180–441 °C), apatite (152–364 °C), tinaksite (218–404 °C) and dalyite (264 °C) suggest a secondary origin for all two-phased FIs, while the high-temperature fluid and melt inclusions (<em>T</em>_h &gt; 400–460 °C) recorded in these minerals formed during the magmatic stage. The coexistence of different types of fluid inclusions in transparent minerals associated with charoite, as well as wide ranges of homogenization temperatures, could be evidence of boiling occurring during the formation of charoitites. Fluid evidence and petrographic observations indicate that both magmatic and hydrothermal processes contributed to the formation of the Sirenevyi Kamen charoite deposit.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"274 ","pages":"Article 107735"},"PeriodicalIF":3.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143561718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A high-performance extreme gradient boosting outlier detection framework for integrating the outputs of diverse anomaly detectors for detecting mineralization-related geochemical anomalies","authors":"Sheng He,&nbsp;Yongliang Chen","doi":"10.1016/j.gexplo.2025.107741","DOIUrl":"10.1016/j.gexplo.2025.107741","url":null,"abstract":"<div><div>In geochemical exploration, the geochemical anomalies identified in the same area by different unsupervised anomaly detection models are often quite divergent. How to combine these divergent geochemical anomalies into reliable mineral prospecting targets is a problem worth studying. In this regard, the extreme gradient boosting outlier detection (XGBOD) framework was adopted to integrate the anomaly scores produced by diverse unsupervised anomaly detection models to construct a high-performance semi-supervised anomaly detection ensemble for detecting mineralization-related geochemical anomalies. In the XGBOD framework, various unsupervised anomaly detection models are built and used to transform input variables into the transformed outlier scores (TOSs), and the important TOSs are then selected and added into the original input data to train the extreme gradient boosting (XGBoost) model, and a high-performance semi-supervised XGBoost model is established finally for detecting mineralization-related geochemical anomalies. The superiority of the XGBOD framework was demonstrated by a case study implemented in the Baishan area (Jilin, China). The <em>K</em>-nearest neighbor, local outlier factor, histogram-based outlier score, one-class support vector machine and isolation forest were used to transform element concentrations to TOSs, and the TOSs were used as the input data of the XGBoost model together with the original input element concentration data. The XGBoost model was finally established to detect mineralization-related geochemical anomalies. The results show that the semi-supervised XGBoost model performs significantly better than the five unsupervised anomaly detection models. Therefore, the XGBOD framework is a viable tool for combining diverse anomaly scores produced by various anomaly detectors to build a high-performance semi-supervised ensemble for detecting mineralization-related geochemical anomalies.</div></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"273 ","pages":"Article 107741"},"PeriodicalIF":3.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}