## 3 Results
### Linear Regression Model Comparison  
Another comparison is presented by utilizing the linear model fit of each curve, as applied in previous studies, who used the linear slope as a test parameter [29; 40]. Figures 5 and 6 present the linear fits of \(R(f)\) and \(L_{n}(f)\) (corresponding to the measured data seen in Figures 1 and 2, respectively). The fitted models deploy simple linear regression and the determination coefficient \(R^{2}\) corresponds to the explained variance of every model fit in the range 0-1 [41]. All fitted models rely on 21 data points of frequency band levels, hence they cannot be further improved with extra data. The \(R^{2}\) values lie between 0.70 and 0.96, which indicate great fitting, except for the impact sound of the reference floor (\(R^{2}\) = 0.01, Figure 6). This model depends only on the intercept, estimated as a mean value at 78.7 dB, while the slope is \(-0.1\) without statistical significance. Airborne sound reduction fits and their slopes in Figure 5 present the linear trends of measurement curves. Floors 1 and 2 have the smallest slopes, after the reference curve, showing their initial trend shifts. Then, floors 3, 4, 5, 6, 8, and 9 show rather similar upward trends, with significant improvements for airborne sound insulation in the presented order. Floors 7 and 10 have the steepest slope, implying radically higher \(R\) values with higher frequency. Floor 10 (with added ceiling) demonstrates similar values to floor 9 at 50-100 Hz, while above 200 Hz, it appears to be the most efficient, with floor 9 clearly being second best. Figure 6 illustrates the linear fits for impact sound curves where the floor cases show decreasing \(L_{n}(f)\) with higher frequencies. The reference CLT floor fit looks almost flat with an average value at 78.7 dB (intercept) having SNQs of \(L_{n,w,100}=L_{n,w,50}=80\) dB and \(L_{n,w}\) = 86 dB without correction terms. The latter value is far from the model's 78.7 dB, which proves the necessity of correction terms with a wide frequency spectrum (including low frequency bands) to yield a representative descriptor value. A first group of floors 1-4 can be observed (highest \(L_{n}(f)\) estimated). Similar behavior appears between floors 9 and 10, which have the best impact sound performance while floors 5-8 have similar slopes  
CLT floors of similar type and thickness considering variations in the wood type as a raw material [21; 31; 42]. Changes in wood material have a high probability of shifting eigenfrequencies [43], which can consequently affect the sound insulation results in 1/3 octave bands. Furthermore, significant variations between the same floor types from different producers have been reported regarding fundamental properties such as the bending stiffness and elasticity modulus [32]. All presented floor configurations with resilient layers and floating masses provide acoustic improvements. However, those improvements are limited for airborne sound reduction index \(R\) below 125 Hz and for impact sound pressure levels \(L_{m}\) below 100 Hz (frequency bands). This is not unexpected and can be justified for the following reasons:  
* The location of the first eigenfrequencies of the combined system of additional layers;
* The overall difficulty to block low frequency noise in structures below 200 Hz [13; 39];
* The inability of CLT elements to resist structural vibrations at low frequencies [42; 43]. The studied configurations with higher thickness and mass provide better sound insulation than others above the first eigenfrequency peaks, i.e., 100-160 Hz. In the airborne sound analysis, a few configurations resonate at 125 Hz (Floors 1-4) or below. However, for impact sound, no such effects occur. Impact sound displays differences in insulation trends (Figures 3 and 6), but overall, most floors follow similar trends, as observed for airborne sound (Figures 1 and 5).