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How successfully is open-source research software adopted? Results and implications of surveying the users of a sensitivity analysis toolbox
11 references·0 citing·31 second hop
How successfully is open-source research software adopted? Results and implications of surveying the users of a sensitivity analysis toolbox (2019)How successfully is open-source research …What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling (2019)What has Global Sensitivity A…VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis (2018)VARS-TOOL: A toolbox for comp…SALib: An open-source Python library for Sensitivity Analysis (2017)SALib: An open-source Python …Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Sensitivity analysis of envir…Most computational hydrology is not reproducible, so is it really science? (2016)Most computational hydrology …Global Sensitivity Analysis of environmental models: Convergence and validation (2016)Global Sensitivity Analysis o…Enhancing reproducibility for computational methods (2016)Enhancing reproducibility for…A Matlab toolbox for Global Sensitivity Analysis (2015)A Matlab toolbox for Global S…The Software Sustainability Institute: Changing Research Software Attitudes and Practices (2013)The Software Sustainability I…GUI–HDMR – A software tool for global sensitivity analysis of complex models (2008)GUI–HDMR – A software tool fo…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Factorial Sampling Plans for Preliminary Computational Experiments (1991)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Model emulation and moment-independent sensitivity analysis: An application to environmental modelling (2011)Sensitivity analysis methods in the biomedical sciences (2020)Surrogate-assisted global sensitivity analysis: an overview (2020)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)The Proof and Measurement of Association between Two Things (1904)Making best use of model evaluations to compute sensitivity indices (2002)Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models (2017)Distribution-based sensitivity analysis from a generic input-output sample (2018)The Logic of Scientific Discovery. (1959)Why Most Published Research Findings Are False (2005)Why Most Published Research Findings Are False (2005)On code sharing and model documentation of published individual and agent-based models (2020)Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach (2020)Promoting an open research culture (2015)Researching Mental Health Disorders in the Era of Social Media: Systematic Review (2017)The future of scientific workflows (2017)FAIR Computational Workflows (2019)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A Fresh Look at Variography: Measuring Dependence and Possible Sensitivities Across Geophysical Systems From Any Given Data (2020)Sensitivity analysis: A discipline coming of age (2021)Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences (1994)The "Stern Review" on the Economics of Climate Change (2006)Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox (2019)An effective strategy for combining variance- and distribution-based global sensitivity analysis (2020)The Exploratory Modeling Workbench: An open source toolkit for exploratory modeling, scenario discovery, and (multi-objective) robust decision making (2017)Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2016Sensitivity analysis of environmental models: A systematic review with practical workflow1,722 cited
  • 2017SALib: An open-source Python library for Sensitivity Analysis1,544 cited
  • 2015A Matlab toolbox for Global Sensitivity Analysis655 cited
  • 2016Enhancing reproducibility for computational methods413 cited
  • 2016Global Sensitivity Analysis of environmental models: Convergence and validation394 cited
  • 2016Most computational hydrology is not reproducible, so is it really science?233 cited
  • 2008GUI–HDMR – A software tool for global sensitivity analysis of complex models210 cited
  • 2019What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling110 cited
  • 2018VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis103 cited
  • 2013The Software Sustainability Institute: Changing Research Software Attitudes and Practices89 cited

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