Sentence examples for data of uncertainty from inspiring English sources

Exact(1)

The detailed data of uncertainty evaluation was listed in Additional file 1: Tables S5, S6.

Similar(59)

Data extraction included author and year, country of analysis, analysis type and model structure, analysis time horizon and perspective, treatment comparators, primary outcomes, definitions of effectiveness, sources of primary clinical data, sources of utility data, treatment of uncertainty, and main findings.

In the UFZ I've been engaged in issues connected with the uncertainty in the hydrological, ecological, and socioeconomic data, models of uncertainty, and how the uncertainties may influence the possibility of achieving sustainable river basin management.

A fuzzy approach was selected which allowed for operation with vague knowledge and data of high uncertainty.

Besides the problem of searching for effective methods for data analysis there are some additional problems with handling data of high uncertainty.

In addition, although AE consists of a random set of data, the role of uncertainty is not fully taken into account in data processing.

The extent of data uncertainty of surface-wave measurements may have significant consequences on 1D seismic response analysis and it may lead to inaccurate estimate of design ground motion.

We are "concerned that these major findings are presented ambiguously within the Executive Summary and are inconsistent with the observations, data, and levels of uncertainty presented and discussed in the body of the draft Assessment Report," states the review.

The SAB is concerned that these major findings as presented within the Executive Summary are ambiguous and appear inconsistent with the observations, data, and levels of uncertainty presented and discussed in the body of the draft Assessment Report.

Variability in the biomonitoring data provides indicators of uncertainty in the intake estimates.

The focus is on exploring the following aspects: clarity of study objective; adequacy of comparison; choice of study perspective and design; measuring and valuation of costs and outcomes; reporting of data sources; handling of uncertainty; presentation of results.

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