Classifying publications from the clinical and translational science award program along the translational research spectrum: a machine learning approach

BACKGROUND: Translational research is a key area of focus of the National Institutes of Health (NIH), as demonstrated by the substantial investment in the Clinical and Translational Science Award (CTSA) program. The goal of the CTSA program is to accelerate the translation of discoveries from the bench to the bedside and into communities. Different classification systems have been used to capture the spectrum of basic to clinical to population health research, with substantial differences in the number of categories and their definitions. Evaluation of the effectiveness of the CTSA program and of translational research in general is hampered by the lack of rigor in these definitions and their application. This study adds rigor to the classification process by creating a checklist to evaluate publications across the translational spectrum and operationalizes these classifications by building machine learning-based text classifiers to categorize these publications. METHODS: Based on collaboratively developed definitions, we created a detailed checklist for categories along the translational spectrum from T0 to T4. We applied the checklist to CTSA-linked publications to construct a set of coded publications for use in training machine learning-based text classifiers to classify publications within these categories. The training sets combined T1/T2 and T3/T4 categories due to low frequency of these publication types compared to the frequency of T0 publications. We then compared classifier performance across different algorithms and feature sets and applied the classifiers to all publications in PubMed indexed to CTSA grants. To validate the algorithm, we manually classified the articles with the top 100 scores from each classifier. RESULTS: The definitions and checklist facilitated classification and resulted in good inter-rater reliability for coding publications for the training set. Very good performance was achieved for the classifiers as represented by the area under the receiver operating curves (AUC), with an AUC of 0.94 for the T0 classifier, 0.84 for T1/T2, and 0.92 for T3/T4. CONCLUSIONS: The combination of definitions agreed upon by five CTSA hubs, a checklist that facilitates more uniform definition interpretation, and algorithms that perform well in classifying publications along the translational spectrum provide a basis for establishing and applying uniform definitions of translational research categories. The classification algorithms allow publication analyses that would not be feasible with manual classification, such as assessing the distribution and trends of publications across the CTSA network and comparing the categories of publications and their citations to assess knowledge transfer across the translational research spectrum

Biribi: disciplining and punishing in the French empire

This article discusses the infamous Bataillons d’Afrique to which French former criminals were sent to complete their duty of military service. The ‘Bat d’Af’ were created to prevent the young male bourgeoisie from having to mix with these ‘undesirables’ and ‘reprobates’, and they were stationed well away from the mainland in France’s North African colonies. This article discusses themes such as discipline, punishment, torture, homosexuality, interracial power relations, and delinquent ‘cultures’ in this imperial context

A model for initiating research data management services at academic libraries

Background: Librarians developed a pilot program to provide training, resources, strategies, and support for medical libraries seeking to establish research data management (RDM) services. Participants were required to complete eight educational modules to provide the necessary background in RDM. Each participating institution was then required to use two of the following three elements: (1) a template and strategies for data interviews, (2) the Teaching Toolkit to teach an introductory RDM class, or (3) strategies for hosting a data class series. Case presentation: Six libraries participated in the pilot, with between two and eight librarians participating from each institution. Librarians from each institution completed the online training modules. Each institution conducted between six and fifteen data interviews, which helped build connections with researchers, and taught between one and five introductory RDM classes. All classes received very positive evaluations from attendees. Two libraries conducted a data series, with one bringing in instructors from outside the library. Conclusion: The pilot program proved successful in helping participating librarians learn about and engage with their research communities, jump-start their teaching of RDM, and develop institutional partnerships around RDM services. The practical, hands-on approach of this pilot proved to be successful in helping libraries with different environments establish RDM services. The success of this pilot provides a proven path forward for libraries that are developing data services at their own institutions

Russian VLBI network “Quasar”: Current status and outlook

This paper presents the past, present and future status of the Russian VLBI network “Quasar”. This network has been developed for at least 20 years by the Institute of Applied Astronomy of the Russian Academy of Sciences (IAA RAS). The equipment installed currently at each “Quasar” station and the facilities for processing observational data are described briefly. The latest results are presented, including the Earth orientation parameters (EOP) determined from the “Quasar” VLBI data and comparison with those from other processing centers. Our future plans to extend the “Quasar” VLBI network to the east and to the west will be carried out by establishing the Ussurijsk station in the Far East and the Russian-Cuban station in the west. They are considered in the context of the Russian section activity in the GGOS project. The expected improvement of the EOP determination accuracy can be obtained within the future configuration of the “Quasar” network, which is proved by simulation. Keywords: Russian VLBI network “Quasar”, VLBI co-location station, Space geodesy technique, Global Geodetic Observing System (GGOS