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A closer look at Fig. 10 indicates the global model had higher modeling efficacy than the seasonal model.
From the kinetic data (Table 2), it was observed that the pseudo second-order model had higher R 2 values than the pseudo first-order model.
The farm systems designed by the model had higher family income than current systems for six of the seven farms studied.
Zhou and Hu (2008) conducted experiments using a hybrid modeling and forecasting approach, which was based on the Grey and Box Jenkins ARMA models, and showed that their proposed model had higher forecasting precision than its single components.
It was more complicated for Scopoletin (Sco): the model had higher predictions at low concentrations and lower predictions at high concentrations by NEd, while it was the direct opposite of predictions by NFd (Fig. 3b).
In this regard, our data are in line with data of Nogueira et al. [32], because patients with CXCL9 rs10336 TT and CXCL10 rs3921 GG genotypes (recessive inheritance model) had higher LSM values and fibrosis stages, possibly due to increased production of these chemokines that could allow the development and maintenance of the infiltration of Th1 cells in liver parenchyma.
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The coefficient of variation was 3.02% (<10%), indicating that the model had high reliability.
The correlation coefficient was 0.995 which mean the model had high fitting capacity.
The model had high sensitivity (81%) and specificity (80%).
Both the re-estimated model have higher classification errors.
Comparing with RBF network, PRBF model has higher prediction accuracy, without the effect of error accumulation.
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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