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Exact(10)
This value determines the number of bits each input and output the adder has.
For classification, the sign of this value determines the predicted class.
This value determines the upper limit of the measured magnetic moment as (1.6{, times, 10^{-3}}, hbox {Am}{^2}), considering the input limit of the analog board ({pm } 10 V.
This value determines whether an event is overall bad (good) for a subject S. If E's value for S is negative, that is, if V S,E) < 0, then E is overall bad for S. If E's value is positive, then E is overall good for S. The more negative (positive) E's value is, the worse (better) E is for S. Consider an example.
This value determines whether the synaptic strength needs to be updated (cf. Table 1A).
This value determines whether a predictor is included or excluded in a model, and corresponds to a P value of about 0.3.
Similar(50)
This value determined the motion within that particular shot.
This value determined in vivo is about four times higher and four times lower, respectively, than the conflicting permeability values resulting from two different in vitro approaches, both incompatible with the measured tmito.
This w value determines the posterior probability of entity of interest.
Half maximal recovery intensity (t1/2) was calculated as the ((average intensity of the plateau) + (postbleach value))/2, and the time corresponding to this intensity value determined from manual inspection of the raw data.
This is the same value determined for kcat1 in the kinetic analysis.
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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