26 papers
This study generates a comprehensive dataset and proposes a penalized percentile ranking system for nearly 7,000 research institutions, balancing the volume of top-cited authors against proxies for research integrity issues like excessive self-citation, publication in discontinued journals, and retractions to provide a more nuanced assessment of institutional impact.
The NIH Common Fund Data Ecosystem (CFDE) provides a collaborative, standards-driven infrastructure that integrates heterogeneous datasets from 18 NIH programs to overcome barriers in data discovery and analysis, thereby enabling cross-disciplinary insights through unified tools and community support.
This bibliometric analysis of over 10 million authors reveals that while overall gender differences in retraction rates are minimal, significant field-specific disparities exist, with structural factors such as discipline, career age, country income, and publication volume being stronger predictors of retraction than gender.
This study demonstrates that shorter and more readable scientific species names significantly increase a species' visibility in both scientific literature and public platforms like Wikipedia, suggesting that orthographic simplicity can help overcome the fickleness of human attention to benefit understudied taxa.
This study demonstrates that traditional physical practice participation significantly enhances vision-related quality of life among junior secondary school students through both direct effects and a serial mediation pathway involving increased exercise self-efficacy and reduced visual function anomalies.
This study demonstrates that the *Journal of Neurotrauma*'s mandatory rigor section significantly improved the reporting of specific transparency items compared to *Experimental Neurology*, though it highlighted a need for further improvements in reporting sex as a biological variable and reagent details.
The Case Western Reserve University Postbaccalaureate Research Education Program (CasePREP) successfully trained 108 scholars from underrepresented backgrounds between 2007 and 2025, achieving high rates of graduate school matriculation and completion with low attrition and significant scientific output, thereby demonstrating the critical value of such programs in diversifying the biomedical research workforce despite the recent termination of NIGMS funding.
This qualitative study of 23 Asian and Asian American student researchers reveals that while they often compartmentalize their cultural identities to meet perceived scientific norms, their backgrounds frequently catalyze research interests, suggesting that educators should reframe cultural heritage as a valuable epistemic resource rather than a bias.
This paper presents a multilingual survey dataset from 105 participants of the 2025 DBCLS BioHackathon in Japan, detailing AI usage patterns, challenges, and demographics across genomics and bioinformatics, accompanied by cleaned data and documentation to support research on AI adoption in science.
This study reveals that widely used generative AI chatbots systematically bias their recommendations for UK neuroscience programmes toward elite institutions and employ masculine-coded language for high-achieving applicants, thereby risking the reinforcement of existing educational and socioeconomic inequalities.
This community-driven study demonstrates that co-developing tailored, locally-grounded illustrations through iterative feedback effectively enhances engagement and understanding of abstract genetics concepts among the Orang Asli of Malaysia and the Turkana of Kenya.
This study demonstrates that a domain-specific generative AI tool, Biodesign Buddy, effectively supports interdisciplinary biodesign education by scaffolding scientific literature research and enhancing foundational understanding for students with limited biology backgrounds.
This bibliometric analysis of African climate-smart agriculture research reveals that despite exponential growth, the field suffers from "structural financial ambiguity" characterized by a critical neglect of financial mechanisms and cognitive oligopolization, which threatens the implementation of climate commitments by prioritizing technical descriptions over actionable financial theorization.
This paper documents a continuous and accelerating decline in the representation of research on eight classic model organisms across scientific literature over the last three decades, driven by a shift toward applied research and an overall expansion of the field, which threatens the future of causal life science discovery and the maintenance of essential research resources.
Despite Nature's 2025 policy requiring sex inclusion reporting, a review of 513 articles reveals that the "male default" persists due to inconsistent experimental design, unbalanced sex ratios, and a lack of meaningful sex-based analysis, indicating that transparency-focused reporting summaries alone are insufficient to ensure rigorous sex inclusion in biomedical research.
Through a multi-stakeholder Delphi consensus study, this paper identifies actionable, feasible strategies for researchers, funders, publishers, and manufacturers to address the widespread waste and unreliability caused by inadequately validated antibodies, while highlighting systemic barriers and proposing a coordinated roadmap for implementation by 2030.
To address the challenge of interpreting whole-genome sequencing data in the high school "yEvo" experimental evolution program, the authors developed the yEvo Mutation Browser, an interactive R Shiny web tool that visualizes mutations and protein structures to help students and researchers understand genetic adaptation while enabling the comparison of new datasets with a shared repository of yeast evolution data.
This study develops and validates an automated L1-regularized logistic regression model using TF-IDF features to detect causal language in scientific abstracts, applying it to a decade of gut microbiome research to reveal significant temporal and thematic heterogeneity in how causal claims are framed.
While biomedical researchers actively utilize preprints for rapid dissemination and networking, their broader adoption is hindered by concerns over evaluation penalties, reliance on author reputation for credibility, and fears regarding scientific integrity, necessitating reforms in assessment frameworks and quality control mechanisms.
Carrierwave is an open, blockchain-based infrastructure that replaces traditional journal articles with granular, cryptographically verified research objects and programmable incentives to accelerate scientific communication, particularly for underrepresented research areas and intermediate findings that are currently excluded from the publication cycle.