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On Fig. 8a and b, it is possible to see the difference in accuracy obtained by the proposed methodology for both dataset using (1~%) of supervision.
Phylogenetic analyses were performed upon 93 and 58 nucleotides of the MIB1 and MIB6 flanking sequence, respectively, applying the HKY+G substitution model inferred for both dataset using the software modeltest 3.7 [3.7.
For both dataset, all three tools were found to show reliability.
For both dataset #4 and #5 Tukey's biweight scaling and T-quantile normalization produce higher AUC values for these approaches.
Moreover, the number of haplotype blocks that contain more than 100 SNPs are larger than the number of SNP fragments for both dataset.
For both dataset generators, if the prior was not accurate enough then the resulting inferred network is worse than when using a naïve prior.
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We received data for years 2000 2009 for both datasets.
The time interval is one second for both datasets.
For both datasets, the examples are 30 s long.
We select 100 anchor points for both datasets.
Fig. 1 Average marked traffic over all videos for both datasets, for conforming users.
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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