Sentence examples for differences in the metrics from inspiring English sources

The difference in the scores may be attributed to the differences in the metrics and TP calculation, i.e., the difference in the metric calculation is due to the fact that we have more score frames and hence we calculate their average, as described at Figure 25 and 25 in Table 1; the temporal processing method used gives us a better target to noise ratio.

Apart from 'all or nothing' preferential statements, the differences in the metrics were discussed in terms of their perceived accuracy (justified or erroneous) in indicating the performance or quality of providers and their interpretability, or perceptions around how easy they were to understand.

We tested for significant differences in these metrics between the three land use zones and between two periods, 1972 1992 and 1993 2001.

Similarly, as part of the evaluation, it is important to assess if the error distributions are statistically different from each other to confirm if the observed differences in the benchmark metrics are real.

In Lake Ontario, female sea lamprey length increased by 7%, but there were no differences in the other metrics.

We found no consistent differences in the measured metrics between the two restoration designs and few differences between restored sites and reference natural marsh stands.

Other than these there were no statistically significant differences in the demographic metrics between each of the groups.

However, this QST-FST comparison is not to be considered a precise test for natural selection, but rather as a coarse assessment to explore if some traits and deme comparisons show consistent patterns of differences in the two metrics.

Based on the methods of analysis for small data sets suggested by Di Stefano et al.[ 37], estimations of the biological importance of the mean differences in the various metrics was determined using Students' t-tests p value, percent difference (PD), and effect size (Hedges' g) as determined in SPSS 16.0 (IBM Corporation, New York, United States).

These three datasets are the most challenging for both aligners, but YAHA has a significantly lower false positive and especially false negative rate, accounting for most of the large difference in these metrics shown in the Totals column.

Much of the variation that we observed could be explained by differences among IBIs in the metrics that contributed most to impaired and unimpaired sites.