Blar i NIVA Open Access Archive på forfatter "Moe, Jannicke"
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Development of a hybrid Bayesian network model for predicting acute fish toxicity using multiple lines of evidence
Moe, Jannicke; Madsen, Anders; Connors, Kristin; Rawlings, Jane; Belanger, Scott; Landis, Wayne; Wolf, Raoul; Lillicrap, Adam David (Peer reviewed; Journal article, 2020)A hybrid Bayesian network (BN) was developed for predicting the acute toxicity of chemicals to fish, using data from fish embryo toxicity (FET) testing in combination with other information. This model can support the use ... -
Evaluation of a Bayesian network for strengthening the weight of evidence to predict acute fish toxicity from fish embryo toxicity data
Lillicrap, Adam David; Moe, Jannicke; Wolf, Raoul; Connors, Kristin A.; Rawlings, Jane M.; Landis, Wayne G.; Madsen, Anders L.; Belanger, Scott E. (Peer reviewed; Journal article, 2020)The use of sh embryo toxicity (FET) data for hazard assessments of chemicals, in place of acute sh toxicity (AFT) data, has long been the goal for many environmental scientists. The FET test was rst proposed as a ... -
Machine learning approaches for predicting health risk of cyanobacterial blooms in Northern European Lakes
Mellios, Nikolaos; Moe, Jannicke; Laspidou, Chrysi (Peer reviewed; Journal article, 2020)Cyanobacterial blooms are considered a major threat to global water security with documented impacts on lake ecosystems and public health. Given that cyanobacteria possess highly adaptive traits that favor them to prevail ...