## 5 Conclusions  
In this paper, the features such as height anomalies, gravity values, CBA, and \((N-\zeta)\) differences determined by the GGI method were analyzed.  
Since the influence of various parameters of the GGI model on the determined height anomalies has been studied many times before, the analyses of this functional were now limited and confirmed a small impact on determined height anomalies accuracy of the DEM resolution and the size of the constant density zones. As a result of the analyses, a slightly better fit of the GGI model to the quasigeoid model of Slovakia was also found, which is probably caused by the slightly higher accuracy of this quasigeoid model. The Polish quasigeoid model used was developed without direct use of gravity data (the EGM08 model fitted to GNSS/levelling points).  
In terms of gravity values, a dependence of the accuracy of the GGI model on all analyzed parameters was shown: The DEM resolution, the point height, the density of gravity data used to build the model, and also on used reference density of topography model. The best results of gravity prediction were characterized by an error of approximately 1 mGal. These results were compared with classical prediction methods (using CBA and topographic-isostatic anomalies supported by Kriging prediction), getting very similar results to the GGI approach. The sensitivity of the classical prediction methods to the model of topographic mass density distribution used for reduction was also confirmed. However, for the best versions (\(\rho_{0}=2670\) kg/m\({}^{3}\)), the classical methods showed slightly better results than GGI method (5 to 10%), in the versions with poorly selected topographic mass density, slightly more favorable prediction results were obtained by the GGI method.  
On the basis of the GGI model, CBA and differences \((N-\zeta)\) were also determined. The strong dependence of resolution of the CBA anomaly model on the size of the constant density zones has been demonstrated, which significantly reduces the quality of such a model. Hence, determining the CBA directly from the GGI model requires a change in the approach of the solution itself (a significant reduction in the size of constant density zones is needed). The crucial importance of the topographic masses density model for both determined values was also indicated. Therefore, for determining these quantities, all available information on topographic mass densities should be used in modelling.  
[PERSON] developed the GGI model and conducted analyses of its accuracy; also prepared the main part of the manuscript. M.O.-W. conducted analyses of gravity interpolation using free air, Bouguer, and topographic-isostatic anomalies. L.P. prepared gravity data for analyses and performed analyses of Bouguer  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Min** & **Max** & **Average** \\ \hline \(\sigma_{\text{CBA}_{\textit{\tiny{$\mathcal{N}$}}}}\) [mGal] & 0.42 & 8.33 & 2.61 \\ \hline \(\sigma_{N-\zeta_{\textit{\tiny{$\mathcal{N}$}}}}\) [cm] & 0.01 & 1.15 & 0.17 \\ \hline \end{tabular}
\end{table}
Table 8: Basic statistics of \(\sigma_{\text{CBA}}\) and \(\sigma_{N-\zeta}\) values.  
anomalies. O.J. conducted analyses of the differences between geoid undulations and height anomalies and prepared Figures. All authors took part in developing the concept of the manuscript and reviewed it. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.