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BO models that incorporate the calculation of Rv are considered "modified" BO PVT models, while for the classical BO models, Rv = 0.

The correlation coefficient lies between 0.552 and 0.932 for the zero-order, parabolic diffusion, and modified Freundlich models, while for the first-order model, they are between 0.983 and 0.987.

For models without age, mean error averaged 0.530 and 0.384 m3 ha−1 yearespectivelyively, for non-parametric and parametric models while for models with age, mean error averaged 0.613 and 0.451 m3 ha−1 yearespectivelyively, for non-parametric and parametric models.

Looser geometric restraints are tested for high-resolution structure models, while for low-resolution structure models only tight geometric restraint weights are tried.

For classmate support, there was a stronger positive effect in the beginning of the follow-up period, in all the above-mentioned models, while for teacher support the results were more complex and with no consistent interpretation.

The complete state space can only be calculated and visualised for small models, while for larger models the calculation is limited to states reachable from a limited set of starting states.

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Comparatively, the median was 0.63 with a 95% CI of 0.52 to 0.73 for clinical models, while those for models combining clinical and gene expression results gave a median of 0.65 with 95% CI of 0.54 to 0.74.

In addition, we verified the results by substituting the BDI for group membership in our models while controlling for age, although this modification led to clearly larger AICs.

Adjusted odds ratios for adverse outcomes were determined by multiple logistic regression models, while controlling for the following factors: maternal age, parity, and education.

3, strong links are more stable in the JWBG1 model than in the JWBG2 model, while for weak links the situation is the opposite.

With a large number of repeated cross-validations our opinion is that the issue of stratification becomes redundant when selecting a model, while for assessing the model it is wise to use stratified cross-validation.

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