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Predicting the probability that a chemical causes steatosis using adverse outcome pathway Bayesian networks (AOPBNs)
Burgoon, L. D., Angrish, M., Garcia‐Reyero, N., Pollesch, N., Zupanic, A., & Perkins, E. (2020). Predicting the probability that a chemical causes steatosis using adverse outcome pathway Bayesian networks (AOPBNs). Risk Analysis, 40(3), 512-523. https://doi.org/10.1111/risa.13423
Communication about micropollutants in drinking water: effects of the presentation and psychological processes
Tobias, R. (2016). Communication about micropollutants in drinking water: effects of the presentation and psychological processes. Risk Analysis, 36(10), 2011-2026. https://doi.org/10.1111/risa.12485
How people perceive and will cope with risks from the diffusion of ubiquitous information and communication technologies
Moser, S., Bruppacher, S. E., & Mosler, H. J. (2011). How people perceive and will cope with risks from the diffusion of ubiquitous information and communication technologies. Risk Analysis, 31(5), 832-846. https://doi.org/10.1111/j.1539-6924.2010.01544.x
Joint persistence of transformation products in chemicals assessment: case studies and uncertainty analysis
Fenner, K., Scheringer, M., & Hungerbühler, K. (2003). Joint persistence of transformation products in chemicals assessment: case studies and uncertainty analysis. Risk Analysis, 23(1), 35-53. https://doi.org/10.1111/1539-6924.00288