Thermohaline forcing and interannual variability of northwestern inflows into the northern North Sea

A long-established, 127 km-long hydrographic section in the northern North Sea at 59.28°N that runs from the eastern coast of Orkney (2.23°W) to the central North Sea (0°) crosses the path of the main inflows of Atlantic water. Data from 122 occupations between 1989 and 2015 are examined to determine the annual cycle and long-term trends of temperature, salinity and depth-varying geostrophic flow across the section. In an average year, the geostrophic flow referenced to the seafloor is at its narrowest (40 km) in winter, during which time it is driven by the strong horizontal salinity gradient; the horizontal temperature gradient is very weak. Velocity exceeds 4 cm s−1, but transport is at a minimum (0.11 Sv). In the deeper water in the east of the section, thermal stratification develops throughout summer and persists until October, whereas the west is tidally mixed all year. The bottom temperature gradient becomes the primary driver of the geostrophic flow, which is fastest (9 cm s−1) in September and broadest (100 km) in October. Maximum transport (0.36 Sv) occurs in October. Throughout the summer, the horizontal salinity gradient weakens, as does its contribution to the flow. However, it nevertheless acts to broaden the flow west of the location of the strongest horizontal temperature gradient. Section-mean de-seasoned temperature is found to be positively correlated to the Atlantic Multidecadal Oscillation and negatively correlated to the North Atlantic Oscillation. These results refine our understanding of the thermohaline forcing of Atlantic inflow into the northern North Sea, particularly in relation to the salinity distribution. Understanding the variability of this inflow is important for understanding the dynamics of the North Sea ecosystem

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

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