Sentence examples for model to predict the consequences of from inspiring English sources

We do not consider here the third possible approach to estimating NP toxicity, computer simulation, because the pathways and mechanisms of the toxic effects of NPs are not known well enough for a computer model to predict the consequences of interactions between NPs and living matter for a wide range of NPs with sufficient reliability.

A causal model serves as an "oracle for interventions" (Pearl, /2009 2000) in the sense that one can use the model to predict the consequences of potential interventions.

The extensive integration of plant metabolic networks revealed by metabolomics demonstrates the importance of establishing a comprehensive model to predict the consequences of perturbations in secondary metabolism on the regulation of primary pathways.

Our results contribute towards an improved understanding of the biological effects of LDR and provide further evidence to suggest that the LNT model may not be the best model to predict the consequences of radiation-induced outcomes over a wide range of doses.

The extended model would, for example, enable us to predict the consequences of different applied drainage rates.

For practical applications, a simplified chemo-mechanical model of CaO hydration is eventually proposed, to predict the consequences of uncombined lime in concrete structures.

A third goal is to emphasize full-scale modeling for the purpose of enabling students to predict the consequences of their design decisions and to learn about construction technologies.

Taken together, models, either mathematical or verbal, are necessary both to predict the consequences of newly discovered processes and to provide new hypotheses to be tested empirically.

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology.

It is difficult to predict the consequences of such a move, however.

We formulate curiosity as the error in an agent's ability to predict the consequence of its own actions in a visual feature space learned by a self-supervised inverse dynamics model.