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Considering the entire range tested, the difference between both tools at all dilutions was <10% which we would consider to be an acceptable difference (fit for purpose).
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This particular difference in the two tools illustrates why it is interesting (and perhaps necessary) to use both tools at different stages of inquiry learning in this domain.
It is important to understand the differences between both tools.
In addition, we suspect that the difference in efficiency between both tools may affect lineage tracing results.
Thus it is argued that the small technical differences between both tools did not impact on the uptake.
The dose-response data generated from this triplicate QCM tool was compared with the aforementioned single unit QCM [ 15], and good parity was observed between them with no statistically significant difference between the different tools at all dilutions tested.
Binomial tests comparing performances in each of the probe tests C, D, and E revealed that the four animals as a group selected the functional tool over the nonfunctional one significantly more often (C: p = 0.006; D: p = 0.038) but they chose between two functional tools at random ( E: p = 0.875).
The overlap between the two tools and the wider scope of the RTI item bank explain why the correlation between quality assessments with both tools was positive, but moderate at best.
Tool failure modes and wear mechanisms for both tools were examined at various cutting conditions.
Comparison between the results from both tools can be used to confirm the functional associations of the interested gene sets.
We note, however, the strong correlation of measurements between the PVAS versus ITAS2010 and DEI.Tak tools at both diagnosis and follow-up, suggesting that, overall, all three tools consistently reflect TA disease activity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com