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

Cannabinoid content and label accuracy of hemp-derived topical products available online and at national retail stores.

IMPORTANCE: Products containing cannabinoids such as cannabidiol (CBD) have proliferated since 2018, when the Agriculture Improvement Act removed hemp (ie, cannabis containing 10% less CBD than advertised), 58% (52 products) were underlabeled (ie, contained >10% more CBD than advertised), and 24% (21 products) were accurately labeled. The median (range) percentage deviation between the actual total amount of CBD and the labeled amount was 21% (−75% to 93%) for in-store products and 10% (−96% to 121%) for online products, indicating that products contained more CBD than advertised overall. THC was detected in 37 of 105 products (35%), although all contained less than 0.3% THC. Among the 37 THC-containing products, 4 (11%) were labeled as THC free, 14 (38%) indicated they contained less than 0.3% THC, and 19 (51%) did not reference THC on the label. Overall, 28% of products (29 products) made therapeutic claims, 14% (15 products) made cosmetic claims, and only 47% (49 products) noted that they were not Food and Drug Administration approved. CONCLUSIONS AND RELEVANCE: In a case series of topical cannabinoid products purchased online and at popular retail stores, products were often inaccurately labeled for CBD and many contained THC. These findings suggest that clinical studies are needed to determine whether topical cannabinoid products with THC can produce psychoactive effects or positive drug tests for cannabis