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On simulated datasets with up to 16 taxa, our method correctly detected recombination breakpoints and the number of recombination events for each breakpoint.
This table shows that after taking into consideration all correlated data, our GTDP method correctly detected 99.0% of the cones, compared to the Garrioch et al. 2012 method which detected 94.5% of the gold standard cones; this difference was found to be significant (Z = 15.0, p<0.00015.0,
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Reliability: how many of the known SSCs does the method correctly detect?
To achieve a quantitative comparison of the methods, we look at three properties (in order of decreasing importance): 1. Reliability: how many of the known SSCs does the method correctly detect?
As it can be observed, despite the complexity of some edge images, the varied size of the constructions, and an imperfect or incomplete border representation of some structures, the proposed method correctly detects most of the rectangular contours.
It can be seen that all three methods correctly detected the reference image.
It can be seen that all three methods correctly detected the reference image whose content is present on the TV screen.
All of the computational methods correctly detected viral sequences in the control sample.
Moreover, 82% of the chemical bonds (i.e. two amino acids interacting with each other) identified by the three methods, have been correctly detected by GeminiDistances.
We provide two simulated examples, a real social network and different sets of power law benchmark networks, to illustrate how our method can correctly detect communities in directed networks.
However, our method can correctly detect inlier and outlier arcs because it iteratively selects inlier arcs and fits an ellipse.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com