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A comparison of the two maps shows very few regions of overlap.
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The resulting maps show very high vulnerabilities.
The RF-derived maps show very low out of bag (OOB) errors (around 10% for both soil groups and soil properties) but relatively high validation error from independent profiles (45% for soil depth, 51% for soil texture).
Interestingly, for A08, both BnaSNDH_05_2010a and BnaSGDH_03_2010a maps showed very high correlations, but the BnaDYDH_05_2010a showed a very poor correlation with the physical B. rapa scaffolds (Table 4).
This map shows very clearly that biodiversity is concentrated around areas with a long history of research: Cuba, Colombia, Belize, Panama, Puerto Rico, and Tobago.
Here's Chen's map showing very limited interest in Twitter in the U.S".
Maps show real things, not imaginary ones.
Figure 8 shows very different results for global and local mapping methods.
The water map images show very poor hyperattenuation in the ablated zone (arrowheads).
For the fish assemblies, the optical mapping results show very low proportions of alignable sequence, and alignable sequence is predominantly in the level 3 category, reflecting local alignments.
All LD maps show a very strong correlation with all other maps (ρ > 0.87), with stronger correlations within population.
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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