## 4 Results
### Analysis and Preliminary Classification of the MS Dataset
The origin of these events is controversial, but they are considered to be caused by atmospheric electromagnetic transients or other electrical disturbances affecting the entire acquisition system [8; 32]. Within the analyzed dataset, a total number of 591 electrical transients were identified (68% of the dataset) and classified as false events. The remaining 273 events, manually classified as MS events, show common recurrent time- and frequency-domain features. These events are characterized by short durations (from less than a second up to a few seconds), impulsive onsets, and a well-defined triangular envelope shape (Figure 6d-f). Their spectral range is concentrated between 30 and 150 Hz, and they were found to occur singularly and in short duration sequences (Figure 6g-i). Several authors have recognized these features as being typical of MS events [8; 15; 21]. In particular, the triangular shape of spectrograms can be interpreted as caused by the attenuation of higher frequencies due to the presence of dense discontinuity networks [8]. During the entire monitoring period, only one small-size rockfall (1 m\({}^{3}\) ca.) occurred in the area close to the monitored rock block (between 9-11 March), but no signals were recorded because the monitoring network was not functioning due to a power interruption [18]. Similarly, no evidence of local earthquakes occurring within a radius of 50 km was found in ambient noise recordings over the whole monitoring period [22]. Nevertheless, even though the analyzed dataset was composed of less than one thousand events, the manual classification might still have been affected by some uncertainties as it was highly dependent on a subjective selection. To evaluate the goodness of the manual classification, a quantitative comparison between the two identified classes was performed by analyzing several characteristic time- and frequency-domain parameters of the signals. In Figure 7, each panel compares couples of parameters that were considered for the investigation of the two clusters. The analysis of the relationship between kurtosis and event durations (bracketed and uniform) highlights how false events are concentrated in the left region of both plots (Figure 7a,b), thus confirming their very short and impulsive onset. In contrast, MS events show distributions characterized by variable durations. This behavior could be derived from the fact that both single events (uniform duration > 1-2 s) and sequences of multiple events (bracketed duration > 3-4 s) coexist within this class. The most evident difference between the kurtosis values of these clusters is the broader variability that characterizes the class of false events, with values ranging from 10\({}^{1}\) up to more than 10\({}^{3}\) (Figure 7a,b). Since the kurtosis of the envelope describes the flatness or peakedness of a random variable distribution compared to a normal distribution, high values of this parameter are expected for impulsive transients, while low values are typical of background noise [21; 55]. By observing the almost linear relationship between the normalized maximum amplitude (A\({}_{\text{max}}\)/A\({}_{\text{mean}}\)) and the Arias intensity (I\({}_{\text{A}}\)), two distinct alignments of MS and false events are evident (Figure 7c), with the latter class characterized by higher A\({}_{\text{max}}\)/A\({}_{\text{mean}}\) values than the former within the same interval of I\({}_{\text{A}}\). In addition, a clear cluster of false events is concentrated at very low A\({}_{\text{max}}\)/A\({}_{\text{mean}}\) and I\({}_{\text{A}}\) values, probably describing noise transients rather than energetic electrical disturbances. Along with these results, the most significant differences observed between the two manually identified classes are shown in panels d and e of Figure 7. In these plots, the spectral content of all events, represented both in terms of peak frequency (f\({}_{\text{max}}\)) and 10-Hz frequency bands (f\({}_{\text{band}}\)), was compared to their A\({}_{\text{max}}\)/A\({}_{\text{mean}}\) values.