To obtain a first simulation of NESTOREv1.0's ability to classify a cluster in the hours immediately following the occurrence of its FSE, we evaluated the performance of the near-real-time module in both the ITA and NEI area. Since the first period of feature calculation of NESTOREv1.0 is currently 6 hours after the occurrence of the FSE, the forecasting of an SSE is limited to those clusters that do not have an event with a magnitude M ≥ MFSE-1 in the first 6 hours after the FSE. Subsequently, 5 clusters for the ITA area and 2 clusters for the NEI area were analyzed, corresponding to the available cases with MFSE≥4 and MFSE≥3.7 in the case of ITA and NEI, respectively. As the final forecasting period, we chose the one corresponding to the best threshold performance obtained for the C_ITAtest and the C_NEItest, which corresponds to one day after the FSE in the case of ITA and 6 hours after the FSE in the case of NEI. We have shown in Fig. 14a the type of clusters analyzed and in Fig. 14b the performance of NESTOREv1.0 corresponding to the last forecasting period.

## 8.1 Application to ITA

For the ITA area, we considered the ML 4.4 Gambettola (type A), ML 4.6 Montagano (type B), ML 4.4 Catania (type B), ML 4.2 Ceneselli (type A) clusters that occurred in 2023 using INGV data (http://terremoti.ingv.it/) (Fig. 14). In addition, we included in the analysis the B-type cluster corresponding to the ML 3.9 Moltelparo event, whose MFSE value was reported as 4.0 in the first week after the FSE (Fig. 14). In such a case, we can test the classification in near-real-time, even when the magnitude of the FSE fluctuates around the given Mth threshold.

In the case of the Gambettola cluster (northern Italy), the FSE with magnitude ML 4.1 occurred at 10:45:41 UTC on January 26, 2023, followed by the SSE at 05:32:51 on January 28 with the same magnitude value. In the first six hours, there are four events with a magnitude of ML 2.1 or more, and the voting of the S, Z, Vm, Q and N2 features after six hours is of type A with a probability P(A) equal to 1. In the following periods, the additional A-type voting of SLCum, QLCum at 12 hours and SLCum2, QLCum2 at 18 hours after the FSE leads to a Bayesian probability of type A P(A) equal to 1 (Figure S6) and then to a correct classification of the cluster for all periods considered (Fig. 14c).

The Montagano B-type cluster is characterised by a FSE of ML 4.6 that occurred on 28 March 2023 at 21:52:42 UTC. The earthquake was clearly felt in the Molise region (central Italy) and neighbouring regions, and the strongest aftershock occurred the following day with a ML of 2.6 at a time interval of just over 6 hours. The latter event turns out to be the only aftershock analysed by NESTOREv1.0 that leads to a zero P(A) probability for S, Z, Q, Vm, N2 at 6 hours and for SLCum at 12 hours (Figure S7). The resulting Bayesian probability that the cluster is type A is correctly equal to 0 from 6 hours to one day after the FSE (Fig. 14d).

The third case analysed concerns a B-type cluster whose FSE had an epicentre about 10 km southeast of the coast of Catania (southern Italy) on April 21, 2023 with ML 4.4. This event, which was about 17 km deep, was widely resonant in the south-eastern part of Sicily and was followed by only two events with ML below 2. Since there is therefore no event with a magnitude greater than MFSE-2, all the features vote for type B from 6 hours to 1 day. It follows that, as in the previous case, the classification of the cluster based on the Bayesian method is correctly type B for all increasing periods from the FSE occurrence onwards.

The fourth case analyzed is the type A cluster, whose FSE with ML 4.2 occurred on October 28, 2023 in the southern part of the Veneto region and was followed three days later by an event of the same magnitude. No event with a magnitude greater than 2.1 occurred in the time window between these events. Consequently, the features and their Bayesian combination result in a P(A) = 0 for each time period leading to a misclassification of the cluster.

The last case corresponds to the type B cluster in Montelparo (Marche region) having a FSE that occurred on November 14, 2023. Its estimated magnitude value was ML 4.0 in the first two weeks and ML 3.9 thereafter. In the first six hours after the FSE, an event with ML greater than 2 occurs, and at 6 hours the P(A) values provided by N2, Vm, Z, Q are equal to 0 and are inherited in the following periods. Even if another event with ML>2.0 occurs after the 6 hours and the features S, SLCum to SLCum2 vote for a cluster of type A, the resulting Bayesian probability P(A) is equal to 0 up to one day, which leads to a correct classification of the cluster.

## 8.2 Application to NEI

In the case of NEI, we analysed in near-real-time the ML 3.9 Zuglio A-type cluster (2021) and the ML 4.5 Klana B-type cluster (2023) using the data from the OGS network and bulletin (http://www.crs.inogs.it/bollettino_new/). In both cases, a report was sent to the head of the OGS Seismological Research Centre (CRS).

The first cluster occurred about 80 km northwest of Udine town. The FSE occurred on October 21, 2021 (ML 3.9) and its SSE (ML 3.0) occurred almost a day apart. Two aftershocks were recorded between these events, one with a magnitude of ML 2.1 and another with a magnitude of ML 1.1, which occurred two and five hours after the FSE respectively. The first of them was considered in the NESTOREv1.0 analysis, which correctly provides a Bayesian probability P(A) for the cluster equal to 1 after 6 hours. In particular, the features S, Q and N2 vote for a cluster A with a P(A) = 1 in the case of S and Q and P(A) = 0.8 in the case of N2.

The second case considered refers to a type B cluster whose FSE with a ML of 4.5 occurred on July 29, 2023 in Klana (Croatia) near the border between Croatia and Slovenia. This event, which was felt in Croatia, Slovenia and north-eastern Italy, was followed by several aftershocks, the strongest of which had a ML of 2.4. As there were no events with a magnitude greater than 2.5, the available N2, S and Q features at 6 hours gave a P(A) = 0, resulting in a correct classification of the cluster in near-real-time.