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Overall, most datasets are well fitted by a combination of both functions, model (m_{4}).
The distribution reveals that most pairwise similarities are rather low with over 80% being < 0.5 and over 60% being < 0.3, suggesting that most datasets are rather diverse.
Therefore, most datasets are either long-term studies of focal populations or broad-scale studies of more limited duration making temporal patterns difficult to detect.
Although record linkage of routinely collected health datasets is a valuable research resource, most datasets are established for administrative purposes and not for health outcomes research.
However, for most domains of research and most scientists, no suitable repositories have existed until very recently, and most datasets are still neither published nor archived.
The performance results on the 9 datasets of GCD [ 16], OG [ 18], CVTree [ 21– 23], ComPhy [ 5], and CGCPhy are shown in Table 3. From the table, we can see that the accuracies of CGCPhy on most datasets are higher than those of other methods except for dataset 4, in which the performance of CGCPhy is a little lower than the ComPhy method.
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The validation proved that most datasets were suitable for subsequent analysis.
Second, there may be reporting bias, as most datasets were from surgically-resected patients only, and exclude patients with biopsy-proved but unresectable MPNST.
Consistently, the independent contribution of ePPID to the total variance of protein evolutionary rate dN explained by all the six principal components in most datasets is comparable to that of the expression-related variables of mRNA abundance and protein abundance (Additional file 1, Table S7).
Most microarray datasets are most similar to our multifactorial data sets, which yielded poorly inferred networks with unsupervised methods.
If most large datasets are useless, why talk about them at all?
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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