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Transparency, bias, and reproducibility across science: a meta-research view
16 references·2 citing·49 second hop
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References

  • 2013Power failure: why small sample size undermines the reliability of neuroscience7,634 cited
  • 2017A manifesto for reproducible science3,368 cited
  • 2012Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling2,240 cited
  • 2009How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data1,909 cited
  • 2011Believe it or not: how much can we rely on published data on potential drug targets?1,885 cited
  • 2016What does research reproducibility mean?1,291 cited
  • 2014How to Make More Published Research True757 cited
  • 2017The Power of Bias in Economics Research634 cited
  • 2020The Hong Kong Principles for assessing researchers: Fostering research integrity545 cited
  • 2018Assessing scientists for hiring, promotion, and tenure461 cited
  • 2021Investigating the replicability of preclinical cancer biology419 cited
  • 2016Enhancing reproducibility for computational methods413 cited
  • 2016Evolution of Reporting P Values in the Biomedical Literature, 1990-2015370 cited
  • 2016Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?334 cited
  • 2021Challenges for assessing replicability in preclinical cancer biology

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308 cited
  • 2020Academic criteria for promotion and tenure in biomedical sciences faculties: cross sectional analysis of international sample of universities241 cited
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    • 2025Gaming the metrics: bibliometric anomalies in global university rankings and the research integrity risk index (RI2)27 cited
    • 2025Evaluating dental AI research papers: Key considerations for editors and reviewers16 cited