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ReCiter: An open source, identity-driven, authorship prediction algorithm optimized for academic institutions.

ABSTRACT: Academic institutions need to maintain publication lists for thousands of faculty and other scholars. Automated tools are essential to minimize the need for direct feedback from the scholars themselves who are practically unable to commit necessary effort to keep the data accurate. In relying exclusively on clustering techniques, author disambiguation applications fail to satisfy key use cases of academic institutions. Algorithms can perfectly group together a set of publications authored by a common individual, but, for them to be useful to an academic institution, they need to programmatically and recurrently map articles to thousands of scholars of interest en masse. Consistent with a savvy librarian's approach for generating a scholar's list of publications, identity-driven authorship prediction is the process of using information about a scholar to quantify the likelihood that person wrote certain articles. ReCiter is an application that attempts to do exactly that. ReCiter uses institutionally-maintained identity data such as name of department and year of terminal degree to predict which articles a given scholar has authored. To compute the overall score for a given candidate article from PubMed (and, optionally, Scopus), ReCiter uses: up to 12 types of commonly available, identity data; whether other members of a cluster have been accepted or rejected by a user; and the average score of a cluster. In addition, ReCiter provides scoring and qualitative evidence supporting why particular articles are suggested. This context and confidence scoring allows curators to more accurately provide feedback on behalf of scholars. To help users to more efficiently curate publication lists, we used a support vector machine analysis to optimize the scoring of the ReCiter algorithm. In our analysis of a diverse test group of 500 scholars at an academic private medical center, ReCiter correctly predicted 98% of their publications in PubMed.

SUBMITTER: Albert PJ

PROVIDER: S-EPMC8016248 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionPatient age and hospital volume have been shown to affect perioperative outcomes after pediatric pyeloplasty. However, there are few multicenter studies that focus on outcomes at teaching hospitals, where many of the operations are performed.ObjectiveThe goal was to determine if surgical approach, age, case volume, or other factors influence perioperative outcomes in a large contemporary cohort.Study designUsing the clinical database/resource manager (CDB/RM) of the University Health-System Consortium (UHC), children who underwent open, laparoscopic, or robotic pyeloplasty from 2011 to 2014 were identified at 102 academic institutions. Surgery type, age, race, gender, insurance type, geographic region, comorbidities, surgeon volume, and hospital volume were measured. Multivariable mixed-effects logistic regression analysis was used to analyze independent variables associated with complication rates, length of stay (LOS), readmission rates, and ICU admission.ResultsA total of 2219 patients were identified. Complication rates were 2.1%, 2.2%, and 3% after open, laparoscopic, and robotic pyeloplasty, respectively. Approximately 12% of patients had underlying comorbidities. Comorbidities were associated with 3.1 times increased odds for complication (p = 0.001) and a 35% longer length of stay (p < 0.001). Age, gender, insurance type, and hospital volume had no effect on complication rates. A trend was seen towards a lower rate of complications with higher surgeon volume (p = 0.08). The mean LOS was 2.0 days in the open pyeloplasty group, 2.4 days in the laparoscopic group and 1.8 days in the robotic group. Patients who underwent robotic surgery had an estimated LOS 11% shorter than those after open surgery (p = 0.03) (Table). Patients aged 5 years and under who had robotic surgery had an estimated LOS 14% shorter than those after open surgery (p = 0.06). ICU admission and hospital readmission were not associated with any variables.DiscussionThe study is limited by the accuracy of the data submitted by the hospitals and is subject to coding error. Complication rates remain low in all three approaches, validating their safety. Patients, including younger patients, had shorter lengths of stay after robotic surgery. The statistically significant differences between approaches were small so clinically there may not be a difference.ConclusionsThis large multicenter analysis demonstrates that patient comorbidity had the greatest impact upon complication rates and length of stay. Previous work showed that the benefits of laparoscopy were limited to older children. However, this large multicenter study suggests that these benefits now extend to young children with the application of robotics.

Project description:Importance:Courtesy authorship is defined as including an individual who has not met authorship criteria as an author. Although most journals follow strict authorship criteria, the current incidence of courtesy authorship is unknown. Objective:To assess the practices related to courtesy authorship in surgical journals and academia. Design, Setting, and Participants:A survey was conducted from July 15 to October 27, 2017, of the first authors and senior authors of original articles, reviews, and clinical trials published between 2014 and 2015 in 8 surgical journals categorized as having a high or low impact factor. Main Outcomes and Measures:The prevalence of courtesy authorship overall and among subgroups of authors in high impact factor journals and low impact factor journals and among first authors and senior authors, as well as author opinions regarding courtesy authorship. Results:A total of 203 first authors and 254 senior authors responded (of 369 respondents who provided data on sex, 271 were men and 98 were women), with most being in academic programs (first authors, 116 of 168 [69.0%]; senior authors, 173 of 202 [85.6%]). A total of 17.2% of respondents (42 of 244) reported adding courtesy authors for the surveyed publications: 20.4% by first authors (32 of 157) and 11.5% by senior authors (10 of 87), but 53.7% (131 of 244) reported adding courtesy authorship on prior publications and 33.2% (81 of 244) had been added as a courtesy author in the past. Although 45 of 85 senior authors (52.9%) thought that courtesy authorship has decreased, 93 of 144 first authors (64.6%) thought that courtesy authorship has not changed or had increased (P?=?.03). There was no difference in the incidence of courtesy authorship for low vs high impact factor journals. Both first authors (29 of 149 [19.5%]) and senior authors (19 of 85 [22.4%]) reported pressures to add courtesy authorship, but external pressure was greater for low impact factor journals than for high impact factor journals (77 of 166 [46.4%] vs 60 of 167 [35.9%]; P?=?.04). More authors in low impact factor journals than in high impact factor journals thought that courtesy authorship was less harmful to academia (55 of 114 [48.2%] vs 34 of 117 [29.1%]). Overall, senior authors reported more positive outcomes with courtesy authorship (eg, improved morale and avoided author conflicts) than did first authors. Conclusions and Relevance:Courtesy authorship use is common by both first and senior authors in low impact factor journals and high impact factor journals. There are different perceptions, practices, and pressures to include courtesy authorship for first and senior authors. Understanding these issues will lead to better education to eliminate this practice.

Project description:BackgroundThe advent of next generation sequencing has opened new avenues for basic and applied research. One application is the discovery of sequence variants causative of a phenotypic trait or a disease pathology. The computational task of detecting and annotating sequence differences of a target dataset between a reference genome is known as "variant calling". Typically, this task is computationally involved, often combining a complex chain of linked software tools. A major player in this field is the Genome Analysis Toolkit (GATK). The "GATK Best Practices" is a commonly referred recipe for variant calling. However, current computational recommendations on variant calling predominantly focus on human sequencing data and ignore ever-changing demands of high-throughput sequencing developments. Furthermore, frequent updates to such recommendations are counterintuitive to the goal of offering a standard workflow and hamper reproducibility over time.ResultsA workflow for automated detection of single nucleotide polymorphisms and insertion-deletions offers a wide range of applications in sequence annotation of model and non-model organisms. The introduced workflow builds on the GATK Best Practices, while enabling reproducibility over time and offering an open, generalized computational architecture. The workflow achieves parallelized data evaluation and maximizes performance of individual computational tasks. Optimized Java garbage collection and heap size settings for the GATK applications SortSam, MarkDuplicates, HaplotypeCaller, and GatherVcfs effectively cut the overall analysis time in half.ConclusionsThe demand for variant calling, efficient computational processing, and standardized workflows is growing. The Open source Variant calling workFlow (OVarFlow) offers automation and reproducibility for a computationally optimized variant calling task. By reducing usage of computational resources, the workflow removes prior existing entry barriers to the variant calling field and enables standardized variant calling.

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ReCiter: An open source, identity-driven, authorship prediction algorithm optimized for academic institutions.

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