Extreme oxygen isotope zoning in garnet and zircon from a metachert block in melange reveals metasomatism at the peak of subduction metamorphism

A tectonic block of garnet quartzite in the amphibolite-facies melange of the Catalina Schist (Santa Catalina Island, California, USA) records the metasomatic pre-treatment of high-delta O-18 sediments as they enter the subduction zone. The block is primarily quartz, but contains two generations of garnet that record extreme oxygen isotope disequilibrium and inverse fractionations between garnet cores and matrix quartz. Rare millimeter-scale garnet crystals record prograde cation zoning patterns, whereas more abundant similar to 200-mu m-diameter crystals have the same composition as rims on the larger garnets. Garnets of both generations have high-delta O-18 cores (20.8 parts per thousand-26.3 parts per thousand, Vienna standard mean ocean water) that require an unusually high-delta O-18 protolith and lower-delta O-18, less variable rims (10.0 parts per thousand-11.2 parts per thousand). Matrix quartz values are homogeneous (13.6 parts per thousand). Zircon crystals contain detrital cores (delta O-18 = 4.7 parts per thousand-8.5 parts per thousand, 124.6 + 1.4/-2.9 Ma) with a characteristic igneous trace element composition likely sourced from arc volcanics, surrounded by zircon with metamorphic age (115.1 +/- 2.5 Ma) and trace element compositions that suggest growth in the presence of garnet. Metamorphic zircon decreases in delta O-18 from near-core (24.1 parts per thousand) to rim (12.4 parts per thousand), in equilibrium with zoned garnets. Collectively, the data document the subduction of a mixed high-delta O-18 siliceous ooze and/or volcanic ash protolith reaching temperatures of 550-625 degrees C prior to the nucleation of small garnets without influence from external fluids. Metasomatism was recorded in rims of both garnet and zircon populations as large volumes of broadly homogeneous subduction fluids stripped matrix quartz of its extremely high oxygen isotope signature. Thus, zoned garnet and zircon in high-delta O-18 subducted sediments offer a detailed window into subduction fluids

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

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 research.Peer reviewe

Extreme oxygen isotope zoning in garnet and zircon from a metachert block in mélange reveals metasomatism at the peak of subduction metamorphism

A tectonic block of garnet quartzite in the amphibolite-facies mélange of the Catalina Schist (Santa Catalina Island, California, USA) records the metasomatic pre-treatment of high-δ18O sediments as they enter the subduction zone. The block is primarily quartz, but contains two generations of garnet that record extreme oxygen isotope disequilibrium and inverse fractionations between garnet cores and matrix quartz. Rare millimeter-scale garnet crystals record prograde cation zoning patterns, whereas more abundant ∼200-μm-diameter crystals have the same composition as rims on the larger garnets. Garnets of both generations have high-δ18O cores (20.8‰–26.3‰, Vienna standard mean ocean water) that require an unusually high-δ18O protolith and lower-δ18O, less variable rims (10.0‰–11.2‰). Matrix quartz values are homogeneous (13.6‰). Zircon crystals contain detrital cores (δ18O = 4.7‰–8.5‰, 124.6 +1.4/−2.9 Ma) with a characteristic igneous trace element composition likely sourced from arc volcanics, surrounded by zircon with metamorphic age (115.1 ± 2.5 Ma) and trace element compositions that suggest growth in the presence of garnet. Metamorphic zircon decreases in δ18O from near-core (24.1‰) to rim (12.4‰), in equilibrium with zoned garnets. Collectively, the data document the subduction of a mixed high-δ18O siliceous ooze and/or volcanic ash protolith reaching temperatures of 550–625 °C prior to the nucleation of small garnets without influence from external fluids. Metasomatism was recorded in rims of both garnet and zircon populations as large volumes of broadly homogeneous subduction fluids stripped matrix quartz of its extremely high oxygen isotope signature. Thus, zoned garnet and zircon in high-δ18O subducted sediments offer a detailed window into subduction fluids

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

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