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Confirmatory experiments confirmed that the model predictions were in good agreement with the experimental results.
Low deviations during training, validating and testing stages confirmed that the model is reliable within the studied range.
The lack of fit obtained for this model was 0.357 which confirmed that the model is highly significant and the experiments are accurate and reliable.
We confirmed that the model could accurately predict viral and host protein levels at extended time points by testing it against experimental data.
Experimentation confirmed that the model developed based on RSM and BBD successfully predicted mycelia production (R2 = 0.9336) and conidia production (R2 = 0.9532).
These compositions were compared with experimentally determined polymeric compositions of recycled milled goods, which confirmed that the model predicts these compositions reasonably well.
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The corresponding residuals were normally distributed which confirmed that the models can be used for the prediction of the retention times and to optimize the separation.
Furthermore, we confirmed that the models conformed to KDM and SMM using the Eclipse Modelling Framework.
Also, the F-statistic confirmed that the models still had ARCH effects.
This further confirmed that the models with random data stratification perform better than those with fixed stratification.
Representative numerical examples confirm that the model accounts for the fracturation qualitative properties.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com