Sentence examples for generation of confidence from inspiring English sources

Lastly, the calculations of slope and intercept found in table 1 of Young et al. [1] would benefit greatly from the generation of confidence intervals from a resampling procedure to determine whether their values differ from random.

Higham et al. (2009) identify this generation of confidence from stimulus distributions as the "direct translation hypothesis".

To investigate individual hypotheses we will also use ordinary least squares regression analysis which will allow the generation of confidence intervals to assist in the interpretation of hypothesised direct and indirect effects and investigation of regions of significance for proposed moderators.

Thus, this type of analysis facilitates the generation of trust and confidence among stakeholders, resulting in a win-win cooperative relationship.

Variant detection was performed using a combination of different sequence read stringencies with the GSMapper software, resulting in the generation of high confidence variant detection (HCDiff) and a less conservative approach to detect all possible sequence variants (AllDiff) (see Methods).

Such interactions raise intriguing questions for future work into the relationship between stimulus processing, subjective awareness and the generation of metacognitive confidence.

This strategy needs to be tested for a large number of sites; however, we anticipate the generation of a confidence network combining specific tools offered by each platform and thus promoting quality management of the services.

This flexibility renders the prediction profile likelihood as a concept promising to resolve one bottleneck in computer-aided simulations of complex systems, the generation of reliable confidence intervals for predictions.

Approximate standard errors (SE) of nucleotide diversities for each gene were obtained by generation of 95% confidence interval (CI) including 1000 random samples and using by default an intermediate recombination rate model (R =10) using the neutral coalescent simulator in DnaSP v5 [ 60].

For the generation of low-confidence data sets, two criteria that influence the compound data integrity, i.e., the confidence level of activity and the type of activity measurements were disregarded in subsequent steps.

Such highly stringent criterion allows the generation of high-confidence functional predictions on the genes included in the functionally characterized RCGs.