9 research outputs found

    Tectonic controls on post-subduction granite genesis and emplacement : the late Caledonian suite of Britain and Ireland

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    Rates of magma emplacement commonly vary as a function of tectonic setting. The late Caledonian granites of Britain and Ireland are associated with closure of the Iapetus Ocean and were emplaced into a varying regime of transpression and transtension throughout the Silurian and into the early Devonian. Here we evaluate a new approach for examining how magma volumes vary as a function of tectonic setting. Available radiometric ages from the late Caledonian granites are used to calculate probability density functions (age spectra), with each pluton weighted by outcrop area as a proxy for its volume. These spectra confirm an absence of magmatic activity during Iapetus subduction between c. 455 Ma and 425 Ma and a dominance of post-subduction magmas between c. 425 Ma and 380 Ma. We review possible reasons why, despite the widespread outcrop of the late Caledonian granites, magmatism appears absent during Iapetus subduction. These include shallow angle subduction or extensive erosion and tectonic removal of the arc. In contrast to previous work we find no strong difference in the age or major element chemistry of post-subduction granites across all terranes. We propose a common causal mechanism in which the down-going Iapetus oceanic slab peeled back and detached beneath the suture following final Iapetus closure. The lithospheric mantle was delaminated beneath the suture and for about 100 km back beneath the Avalonian margin. While magma generation is largely a function of gravitationally driven lithosphere delamination, strike-slip dominated kinematics in the overlying continental crust is what modulated granitic magma emplacement. Early Devonian (419–404 Ma) transtension permitted large volumes of granite emplacement, whereas the subsequent Acadian (late Early Devonian, 404–394 Ma) transpression reduced and eventually suppressed magma emplacement

    Multimodal Analgesia for Perioperative Management of Patients presenting for Spinal Surgery

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    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press
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