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(For other implementations of outlier detection, see Ref. [ 26, 30].) The algorithm in this study uses the measured standard deviation instead of the pooled standard deviation for spots for which the pooling model may not hold.
Section 5 explains the use of the neural pooling model.
The synclinal CBM pooling model from the Qinshui Basin in China is illustrated in Fig. 7.
When P > 0.05 in Q statistic or I < 50%, the fixed pooling model (Mantel-Haenszel) was conducted; if not, the random pooling model (M-H heterogeneity) was used.
Our pooling model is deliberately vague (i.e., general) in order to provide a generous test of substitution.
This model uses information from all objects and thus, by our definition, is a pooling model, not simple substitution.
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Pooling models take input from more than one object and may perform any computation to produce the response.
Unpooled substitution is simple substitution, but there are other, more complicated substitution models whose responses depend on multiple letters, and they are thus pooling models, by our definition.
Estimated kinetic parameters of the two-pool model are presented in Table 4.
We also developed a "pooled" model across these sampling periods to provide an estimate of an annual average.
The pool model is the most scalable one and meta-workflows are only available in nested workflows and workflow conversion.
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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