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The approach predicted that in 60% of the administrations both a 100-mg and a 50-mg vial would be required.
In addition, the USLE-M approach predicted that the deposition that occurred when the slope gradient changed from 9% to 4.5% midway down the slope was much greater than the amount predicted using RUSLE2.
The fitness approach predicted that thymidylate synthase was equally detrimental for both models (selectivity score=1).
While the machine learning approach predicted that half the genes in the genome had a redundant paralog, most genes had no more than two other highly redundant paralogs.
For example, the machine learning approach predicted that 50% of genes are not buffered by paralogous redundancy but reverse genetic screens rarely achieve such a high rate of phenotype discovery.
The gene-deletion approach predicted that 12 enzymes are essential in both networks (Table 1), thus indicating a possible metabolic hepatic impairment caused by the inhibition of homologous enzymes.
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Such an approach predicts that, when more than one behaviour is possible, the behaviour chosen will be the one with the largest combination of expected success and value.
The 'Regression 1' approach predicts that diameter increment continues to increase with increasing tree diameter also in very large trees.
The cognitive approach predicts that only p(C) should influence the illusion.
This approach predicts that the halogenases have only two histidine ligands instead of the canonical 2-His-1-carboxylate ligand set for FeII that characterizes the oxygenases.
Our approach predicts that mutants in these Ctf4-interacting proteins would mimic some of the genetic interactions of ctf4 Δ with cancer-gene orthologs.
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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