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We develop heuristic methods with performance guarantees using three approaches: (i) relaxation rounding, (ii) water filling, and (iii) greedy packing.
Developing fast methods with performance similar to expensive flux-based methods has been a challenge.
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In this section, we demonstrate the performance capacity of the proposed method with performance test results.
Table 2 provides condensed rankings for the 22 methods together with performance statistics for each method obtained by averaging over the 2000 summary trees produced by each method.
Finally, we compared the performance of our methods with the performance of four publicly available SCL predictors, and demonstrated that our novel approach performs as well as or better.
BD and ZF are suboptimal methods with tolerable performance degradation and their lower complexities make them easier to implement.
The need for validation of behavioural and psychometric methods with task performance and the use of cognitive-perceptual-motor modelling are discussed.
Of those 29 applications, only seven (or eight) implement one of the methods with good performance in [12], [13].
Interestingly, those methods with good performance for separating homologs from non-homologs (MCC>0.86) were much weaker at distinguishing DS from common homologs (MCC<0.24) than those methods with relatively poor performance (Fig. 2c).
Intra- and inter-laboratory reproducibility varied between methods with poorest performance seen with BHI vancomycin.
Between these extremes there is a group of methods with intermediate performance.
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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