M
Michael McWilliams
Researcher at University of Michigan
Publications - 5
Citations - 1314
Michael McWilliams is an academic researcher from University of Michigan. The author has contributed to research in topics: Expert elicitation & Algal bloom. The author has an hindex of 4, co-authored 5 publications receiving 1110 citations.
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Journal ArticleDOI
Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions
Anna M. Michalak,Eric J. Anderson,Dimitry Beletsky,Steven Boland,Nathan S. Bosch,Thomas B. Bridgeman,Justin D. Chaffin,Kyung Hwa Cho,Rem Confesor,Irem Daloğlu,Jospeh DePinto,Mary Anne Evans,Gary L. Fahnenstiel,Lingli He,Jeff C. Ho,Liza K. Jenkins,Liza K. Jenkins,Thomas H. Johengen,Kevin C Kuo,Elizabeth LaPorte,Xiaojian Liu,Michael McWilliams,Michael R. Moore,Derek J. Posselt,R. Peter Richards,Donald Scavia,Allison L. Steiner,Edward M. Verhamme,David M. Wright,Melissa A. Zagorski +29 more
TL;DR: It is shown that long-term trends in agricultural practices are consistent with increasing phosphorus loading to the western basin of the lake, and that these trends, coupled with meteorological conditions in spring 2011, produced record-breaking nutrient loads.
Journal ArticleDOI
Using expert elicitation to link foodborne illnesses in the United States to foods.
TL;DR: This paper used expert elicitation to attribute U.S. foodborne illnesses caused by the nine FoodNet pathogens, Toxoplasma gondii, and norovirus to consumption of foods in 11 broad categories.
Journal ArticleDOI
Elicitation from Large, Heterogeneous Expert Panels: Using Multiple Uncertainty Measures to Characterize Information Quality for Decision Analysis
TL;DR: A formal protocol and a suite of uncertainty measures are developed to take advantage of variation in individual expert uncertainty and heterogeneity among experts as a means of quantifying and comparing sources of uncertainty about parameters of interest.
Foodborne Illnesses to Their Food Sources Using Large Expert Panels to Capture Variability in Expert Judgment
TL;DR: A formal protocol for expert elicitation with large, heterogeneous expert panels is developed to take advantage of variation in individual expert uncertainty and heterogeneity among experts as a means of quantifying and comparing sources of uncertainty about parameters of interest.
Attributing U.S. Foodborne Pathogen Illness to Food Consumption
TL;DR: In this article, a formal protocol for expert elicitation with large, heterogeneous expert panels was developed to take advantage of variation in individual expert uncertainty and heterogeneity among experts as a means of quantifying and comparing sources of uncertainty about parameters of interest.