The phrase "assessing uncertainty" is correct and usable in written English.
You can use it in contexts where you are evaluating or analyzing the level of uncertainty in a situation, data, or decision-making process.
Example: "In our research, we are assessing uncertainty in the climate models to better understand potential future scenarios."
Alternatives: "evaluating uncertainty" or "analyzing uncertainty".
Because uncertainties exist in all lines of scientific endeavor, each source of uncertainty across these areas should be considered in assessing uncertainty in the overall risk assessment.
Similarly, the importance of considering interindividual variability in assessing uncertainty associated with chemical risk assessments of noncancer effects has been recognized (Hattis and Silver 1994).
Two General Circulation Models (GCMs) with multiple ensemble integrations were used as a basis for assessing uncertainty in the climate projections.
The method combines the exact (non-asymptotic) Bayesian way of assessing uncertainty with the unbiasedness emphasized in the classical frequentist approach.
Questions related to assessing uncertainty and considering multiple objectives are tackled within the axiomatic structures of MAUT (Multi-attribute Utility Theory).
The primary intent of this research is to identify and demonstrate a quantitative methodology for assessing uncertainty in a Physics-of-Failure (PoF) model of a vibrating environment.
Assessing uncertainties in models due to different sources of errors is crucial for advancing urban drainage modelling practice.
The development of appropriate ground-based validation techniques is critical to assessing uncertainties associated with satellite data-based products.
This understanding should not be conditional on the expertise of the recipient, nor should it depend on the person(s) assessing uncertainties.
Two challenges in such tracer-based estimates are (i) accounting for the different modes of transport in the unsaturated zone (USZ), and (ii) assessing uncertainties.
This simplifies the process of assessing uncertainties about soil data because characteristic uncertainty models can be defined for each data type.
