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Reproducibility and Replicability in Science
0 references·16 citing·49 second hop
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A Systematic Review and Meta-Analysis of Survey Data (2009)Strong Evidence for Gender Differences in Risk Taking (2011)The Hong Kong Principles for assessing researchers: Fostering research integrity (2020)Protecting against researcher bias in secondary data analysis: challenges and potential solutions (2022)Big little lies: a compendium and simulation of p -hacking strategies (2023)Evidence of questionable research practices in clinical prediction models (2023)Big Science and Big Data in Biology: From the International Geophysical Year through the International Biological Program to the Long Term Ecological Research (LTER) Network, 1957–Present (2010)The Rise of Big Data: How It’s Changing the Way We Think about the World (2014)Climate tipping points — too risky to bet against (2019)Conceptualizing the analysis-readiness for the next-generation SDI through the Open Geospatial Engine (OGE) (2026)The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies (2007)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Rayyan—a web and mobile app for systematic reviews (2016)The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool (2024)Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning (2025)GAIDeT (Generative AI Delegation Taxonomy): A taxonomy for humans to delegate tasks to generative artificial intelligence in scientific research and publishing (2025)Investigating the replicability of preclinical cancer biology (2021)Replication concerns in sports and exercise science: a narrative review of selected methodological issues in the field (2022)Reproducibility in Neuroimaging Analysis: Challenges and Solutions (2022)
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The fundamental principles of reproducibility
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