Search alternatives:
values decrease » values increased (Expand Search), largest decrease (Expand Search)
i largest » _ largest (Expand Search), i large (Expand Search)
via large » a large (Expand Search)
c also » _ also (Expand Search), can also (Expand Search)
values decrease » values increased (Expand Search), largest decrease (Expand Search)
i largest » _ largest (Expand Search), i large (Expand Search)
via large » a large (Expand Search)
c also » _ also (Expand Search), can also (Expand Search)
-
41
-
42
-
43
ROC curves separated by mutations that decrease in volume from mutations that increase in volume.
Published 2019“…The tables on the right list the area under the curve (AUC) values along with corresponding 95% confidence interval (CI) for the AUCs.…”
-
44
S1 data_Hazen Main and Blister 2017 absolute diatom counts from Contrasting the ecological effects of decreasing ice cover versus accelerated glacial melt on the High Arctic's largest lake
Published 2020“…Lake Hazen, the High Arctic's largest lake, has received an approximately 10-fold increase in glacial meltwater since its catchment glaciers shifted from net mass gain to net mass loss in 2007 CE, concurrent with recent warming. …”
-
45
-
46
AUC statistics as calculated from simulated time series. Each statistical metric was calculated within sliding windows, throughout the pre-critical interval. We considered five-, fifteen-, and thirty-day sliding windows. Given that the temperature of the system increased to 12°C on day sixty, we also considered three pre-critical intervals: Days 1 to 60, Days 20 to 60, and Days 30 to 60. To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre
Published 2025“…To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre</p>…”
-
47
-
48
-
49
-
50
Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics
Published 2022“…More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.…”
-
51
-
52
-
53
-
54
-
55
-
56
-
57
-
58
-
59
-
60