Sentence examples for metrics which may from inspiring English sources

Fantasy about successes, defined by metrics which may mean nothing, and are often falsified, which support false self concepts.

This can be assessed using a number of metrics, which may vary based on the dataset and study objectives.

In the present study we formally identify and evaluate metrics which may be used to predict the detection difficulty of a given model.

Another limitation that may have resulted in exposure misclassification was the relatively simple proximity and distance-weighted emission metrics, which may not capture the complex and asymmetric exposure patterns that can result from local meteorological, facility, and terrain characteristics.

The overall success of participants in a sub-challenge can be measured by the median Z-score of the scoring metrics, which may be used to quantify the amount of predictive signal available in the provided data for a given classification problem.

This lack of association could reflect limitations of such metrics, which may be insufficiently sensitive for capturing heterogeneity across high-biomass areas such as tropical forests at fine spatial scales [ 82] and will be unable to detect other key human impacts to gibbons such as localised hunting.

Amosvalidate is a software package designed to identify mis-assemblies based on a variety of metrics, each of which may indicate a poor assembly.

This can be extended to learning nonlinear distance metrics in the future, which may lead to further performance improvements.

However, the statistical validity of meta-analysis depends on a degree of homogeneity between studies, not least in terms of their outcome metrics, [ 1, 2] which may be unrealistic outside the world of clinical trials.

Given our interest in examining indicators on a cross-country basis, we required standardised metrics reported by all countries, which may have resulted in the selection of less than ideal metrics for some variables.

We are indeed in this really weird "metric moment" where something with bigger metrics is interpreted as better, which may or may not actually be the case.