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<jats:p>The Jenkyns Event (~183 Ma) represents an exceptional warming period in the Jurassic, which is characterized by intense environmental and climate perturbation. The eruption of the Karoo‐Ferrar Large Igneous Province (K‐F LIP) triggered pronounced carbon isotope negative excursion (N‐CIE) in exogenic carbon reservoirs, global widespread organic carbon burial and extensive ocean anoxia. However, the synchronic coupling relationship between the carbon release, volcanic activity, and intense weathering induced by the K‐F LIP during this period remains poorly understood. In this study, detailed sedimentologic and geochemical studies were conducted on the terrestrial stratigraphy of the Lower Jurassic Fuxian Formation in the Ordos Basin. Three spore‐pollen assemblages have been identified, with the <jats:italic>Cyathidites‐Deltoidospora‐Chasmatosporites</jats:italic> assemblage suggesting a Pliensbachian age, the <jats:italic>Classopollis‐Cycadopites‐Chasmatosporites</jats:italic> assemblage indicating an early to middle Toarcian age, and the <jats:italic>Cyathidites‐Cycadopites‐Psophosphaera</jats:italic> assemblage indicating a late Toarcian age. The lower part of the <jats:italic>Classopollis‐Cycadopites‐Chasmatosporites</jats:italic> assemblage shows a negative CIE with a magnitude of 2.7‰, accompanied by organic carbon enrichment. Mercury concentrations and Hg/total organic carbon ratios also show peaks during the initial stage of the carbon isotope negative shift, implying a synchrony between volcanic activities and carbon perturbation. Furthermore, the Chemical Index of Alteration value has reached its maximum and the kaolinite content shows a sharp increase at the same position as the carbon isotope negative shift initiation, indicating a simultaneous enhancement of continental weathering during volcanic activity. The changing patterns of the continental weathering intensity encompassing the Jenkyns Event also indicate that continental weathering may have functioned as a significant approach to counteract the greenhouse effect caused by substantial volcanic CO<jats:sub>2</jats:sub> emissions.</jats:p>

<jats:p>Rock mass classification (RMC) systems in the realm of rock slope engineering have gathered a lot of attention. The present review article delves into the major RMC systems, elucidating their fundamental principles, key parameters and practical applications. Among the various RMC systems for rock slope designing, Romana's Slope mass rating (SMR) was found to be the most comprehensive; therefore, the focus of the discussion centres around the SMR method. The article provides a crisp overview of the major advancements, evolution and potential challenges of SMR. The radical concept of wedge failure in SMR and the use of continuous functions are discussed in detail. A thorough discussion is provided on the efforts made by different researchers, encompassing the inclusion of novel factors such as slope height, heterogeneity in rock mass or lithology, weighted consideration of existing discontinuities, fuzzy sets and overburden thickness. Various automated calculation techniques and empirical correlations of SMR with other classification systems and rock engineering parameters are also outlined. Moreover, a critical examination of the variations among major extensions of SMR and their geotechnical relevance have also been discussed. Based on a meticulous assessment of the susceptibility to toppling failure in SMR, two sub‐factors to include block shape and interlayer slip between discontinuities have been suggested. These sub‐factors were validated by Goodman's tests for toppling failure. The scope of future projections or possible aspects for revisiting and refinement of the SMR method are suggested to enhance the applicability of the method under a diverse initial set of geotechnical conditions.</jats:p>

<jats:p>Considering the rapid expansion of the economy and the increasing demand for infrastructure development, the scale of the tunnelling is expanding, and tunnel is inevitably excavated under unfavourable geological conditions. Consequently, this brings multitude of risks and challenges to tunnels and tunnelling. This paper summarizes the engineering issues associated with five unfavourable geological conditions: soft soil strata, soft and hard composite strata, spatially variable strata, karst strata and subsea conditions. Various analysis methods for deformation problem of tunnel and tunnelling under these unfavourable geological conditions are discussed. The mechanisms of the progressive failure of tunnel faces and collapses of caves in karst tunnels are also presented, as well as the risk assessments and prevention strategies for karst tunnel and water inrush occurrences of subsea tunnel. Furthermore, the analysis of the response of subsea tunnels to dynamic loads such as wave forces and earthquakes is summarized. Additionally, the analysis and prevention techniques for constructing subsea tunnels in fault zones are also considered. Finally, this paper offers a glimpse into potential research directions for future analysis relevant to the topic discussed, aiming to provide guidance for secure construction and maintenance tunnels under unfavourable geological conditions.</jats:p>

<jats:p><jats:mixed-citation publication-type="miscellaneous">Retraction: ‘’ by <jats:string-name><jats:given-names>Rabin</jats:given-names> <jats:surname>Chakrabortty</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Subodh Chandra</jats:given-names> <jats:surname>Pal</jats:surname> </jats:string-name>, <jats:italic>Geol J</jats:italic> <jats:year>2023</jats:year>, <jats:volume>58</jats:volume>:<jats:fpage>3544</jats:fpage>–<jats:lpage>3576</jats:lpage>.</jats:mixed-citation> The above article, published online on 13 March 2023 in Wiley Online Library (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1002/gj.4709">https://onlinelibrary.wiley.com/doi/full/10.1002/gj.4709</jats:ext-link>) has been retracted by agreement between the journal's Editors in Chief, Ian D. Somerville and Yunpeng Dong, and John Wiley &amp; Sons Ltd.</jats:p><jats:p>The retraction has been agreed following concerns raised by a third party. Further investigation by the publisher has found manipulation of the peer review process. The retraction is warranted due to the compromised integrity of the article's peer review.</jats:p>

<jats:p><jats:mixed-citation publication-type="miscellaneous">Retraction: ‘’ by <jats:string-name><jats:given-names>LiJie</jats:given-names> <jats:surname>An</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>XiuJing</jats:given-names> <jats:surname>Jiang</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Zhen</jats:given-names> <jats:surname>Liu</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Qiong</jats:given-names> <jats:surname>Li</jats:surname> </jats:string-name>, <jats:italic>Geol J</jats:italic> <jats:year>2023</jats:year>, <jats:volume>58</jats:volume>:<jats:fpage>3310</jats:fpage>–<jats:lpage>3325</jats:lpage>.</jats:mixed-citation> The above article, published online on 9 July 2023 in Wiley Online Library (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1002/gj.4787">https://onlinelibrary.wiley.com/doi/full/10.1002/gj.4787</jats:ext-link>) has been retracted by agreement between the journal's Editors in Chief, Ian D. Somerville and Yunpeng Dong, and John Wiley &amp; Sons Ltd.</jats:p><jats:p>The retraction has been agreed following concerns raised by a third party. Further investigation by the publisher has found manipulation of the peer review process. The retraction is warranted due to the compromised integrity of the article's peer review.</jats:p>

<jats:p><jats:mixed-citation publication-type="miscellaneous">Retraction: ‘’ by <jats:string-name><jats:given-names>Paramita</jats:given-names> <jats:surname>Roy</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Subodh Chandra</jats:given-names> <jats:surname>Pal</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Rabin</jats:given-names> <jats:surname>Chakrabortty</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Asish</jats:given-names> <jats:surname>Saha</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Indrajit</jats:given-names> <jats:surname>Chowdhuri</jats:surname> </jats:string-name>, <jats:italic>Geol J</jats:italic> <jats:year>2022</jats:year>, <jats:volume>58</jats:volume>:<jats:fpage>3487</jats:fpage>–<jats:lpage>3514</jats:lpage>.</jats:mixed-citation> The above article, published online on 9 December 2022 in Wiley Online Library (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1002/gj.4649">https://onlinelibrary.wiley.com/doi/full/10.1002/gj.4649</jats:ext-link>) has been retracted by agreement between the journal's Editors in Chief, Ian D. Somerville and Yunpeng Dong, and John Wiley &amp; Sons Ltd.</jats:p><jats:p>The retraction has been agreed following concerns raised by a third party. Further investigation by the publisher has found manipulation of the peer review process. The retraction is warranted due to the compromised integrity of the article's peer review.</jats:p>

<jats:p><jats:mixed-citation publication-type="miscellaneous">Retraction: ‘’ by <jats:string-name><jats:given-names>Indrajit</jats:given-names> <jats:surname>Chowdhuri</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Subodh Chandra</jats:given-names> <jats:surname>Pal</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Paramita</jats:given-names> <jats:surname>Roy</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Rabin</jats:given-names> <jats:surname>Chakrabortty</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Asish</jats:given-names> <jats:surname>Saha</jats:surname> </jats:string-name>, <jats:string-name><jats:given-names>Manisa</jats:given-names> <jats:surname>Shit</jats:surname> </jats:string-name>, <jats:italic>Geol J</jats:italic> <jats:year>2023</jats:year>, <jats:volume>58</jats:volume>:<jats:fpage>3515</jats:fpage>–<jats:lpage>3543</jats:lpage>.</jats:mixed-citation> The above article, published online on 16 March 2023 in Wiley Online Library (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1002/gj.4729">https://onlinelibrary.wiley.com/doi/full/10.1002/gj.4729</jats:ext-link>) has been retracted by agreement between the journal's Editors in Chief, Ian D. Somerville and Yunpeng Dong, and John Wiley &amp; Sons Ltd.</jats:p><jats:p>The retraction has been agreed following concerns raised by a third party. Further investigation by the publisher has found manipulation of the peer review process. The retraction is warranted due to the compromised integrity of the article's peer review.</jats:p>

<jats:p><jats:mixed-citation publication-type="miscellaneous">Retraction: ‘’ by <jats:string-name><jats:given-names>Yong</jats:given-names> <jats:surname>Xu</jats:surname> </jats:string-name>, <jats:italic>Geol J</jats:italic> <jats:year>2023</jats:year>, <jats:volume>58</jats:volume>:<jats:fpage>3288</jats:fpage>–<jats:lpage>3300</jats:lpage>.</jats:mixed-citation> The above article, published online on 26 July 2023 in Wiley Online Library (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1002/gj.4825">https://onlinelibrary.wiley.com/doi/full/10.1002/gj.4825</jats:ext-link>) has been retracted by agreement between the journal's Editors in Chief, Ian D. Somerville and Yunpeng Dong, and John Wiley &amp; Sons Ltd.</jats:p><jats:p>The retraction has been agreed following concerns raised by a third party. Further investigation by the publisher has found manipulation of the peer review process. The retraction is warranted due to the compromised integrity of the article's peer review.</jats:p>

<jats:p>The development of earth fissures, which are linear fractures with openings or offsets on the land surface, can severely affect landforms, especially in urban areas, in the form of earthquakes causing major concern on human lives as well as damage to infrastructures. Thus, an early warning map for lands susceptible to earth fissures can better equip planners for formulating mitigation strategies. In this study, we focus on the Damghan Plain in Iran for preparation of earth fissure susceptible maps using several topographical, hydrological, geological and environmental conditioning factors. In order to train these conditioning factors and preparation of earth fissure susceptibility maps, 124‐earth fissure field‐based samples, for training and validation purposes, were used by random subspace (RS) model based on four other machine learning ensemble methods such as RS‐Naïve‐Bayes Tree (NBTree), RS‐alternating decision tree (ADTree), RS‐Fisher's Linear Discriminant Function (FLDA) and RS‐Logistic model tree (LMT). From the validation technique, the receiver operating characteristic (ROC) curve performance test demonstrates that the RS‐NBTree model was the best suited with area under curve (AUC) = 0.974 followed by RS‐ADTree (AUC = 0.966), RS‐LMT (AUC = 0.954), RS‐FLDA (AUC = 0.948) and RS (AUC = 0.923). The results from our study can be useful for environmental management and risk reduction.</jats:p>

<jats:p>In the process of landslide susceptibility prediction (LSP) modelling, there are some problems in the model dataset relating to landslide and non‐landslide samples, such as landslide sample errors, subjective randomness and low accuracy of non‐landslide sample selection. In order to solve the above problems, a semi‐supervised machine learning model for LSP is innovatively proposed. Firstly, Yanchang County of Shanxi Province, China, is taken as the study area. Secondly, the frequency ratio values of 12 environmental factors (elevation, slope, aspect, etc.) and the randomly selected twice non‐landslides are used to form the initial model datasets. Thirdly, an extreme gradient boosting (XGBoost) model is adopted for training and testing the initial datasets, so as to produce initial landslide susceptibility maps (LSMs) which are divided into very low, low, moderate, high and very high susceptibility levels. Next, the landslide samples in initial LSMs with very low and low susceptibility levels are excluded to improve the accuracy of landslide samples, and the unlabelled twice non‐landslide samples in initial LSMs with low and very low susceptibility levels are randomly selected to ensure the accuracy of non‐landslide samples. These new obtained landslide and non‐landslide samples are reimported into XGBoost model to construct the semi‐supervised XGBoost (SSXGBoost) model. Finally, accuracy, kappa coefficient and statistical indexes of susceptibility indexes are adopted to assess the LSP performance of XGBoost and SSXGBoost models. Results show that SSXGBoost model has remarkably better LSP performance than that of XGBoost model. Conclusively, the proposed SSXGBoost model effectively overcomes the problems that the accuracy of landslide samples needs to be further improved and that non‐landslide samples are difficult to select accurately.</jats:p>