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Cosmic ray data collected by the KASCADE air shower experiment arecompetitive in terms of quality and statistics with those of modernobservatories. We present a novel mass composition analysis based on archivaldata acquired from 1998 to 2013 provided by the KASCADE Cosmic ray Data Center(KCDC). The analysis is based on modern machine learning techniques trained onsimulation data provided by KCDC. We present spectra for individual groups ofprimary nuclei, the results of a search for anisotropies in the event arrivaldirections taking mass composition into account, and search for gamma-raycandidates in the PeV energy domain.

New insights from old cosmic rays: A novel analysis of archival KASCADE data