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The difference is largest near 97% sensitivity where ETA network diffusion has 4-fold fewer false positives (90% vs 60% accuracy).
The similarity within groups is larger than across the population as a whole, and this difference is largest around the peak of g (note the logarithmic scale, the difference is around ten times larger).
The difference is largest for polarity and size.
This difference is largest for the forelegs and is very small for the hindlegs.
Focusing on the size of the coefficients, the difference is largest for law and smallest for economics.
For all six starting conditions, the iterative version outperforms the non-iterative, and the difference is largest when the starting condition has the least number of terms used in training (i.e. starting condition #1, #2), and can be as many as 1000 terms.
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The flow is stronger when that temperature difference is large.
You then compare the outcomes, and if the difference is large enough, exceeding the bounds of chance or natural variation, the result is said to be statistically significant.
However, when h T is small, the difference is large.
The performance difference is larger at low SNR values.
So the oil recovery difference is larger than that of ordinary heavy oil.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com