L'Intelligenza Artificiale come Rilevatore di Anomalie Sistemiche nei Testi Classici: Sparagmós Geografico, Anacronismi Stratigrafici e Silencing Informativo tra Filologia Computazionale e Consilienza Archeometrica

AI identifies systemic anomalies in classical texts, revealing structural contradictions between Bronze Age reality and later Hellenic/Roman narratives. The study challenges the traditional 'harmonizing paradigm' by using a Four-Tier Epistemic Demarcation Matrix to filter mechanical errors, literary tropes, and detect three classes of anomalies: geographic inconsistencies (sparagmós), stratigraphic anachronisms, and informational silencing. Validated through archaeometric proxies like radiocarbon dating and dendrochronology, the model demonstrates that North African fleets' reliance on Sardinian-Corsican timber during the Late Bronze Age was logistically absolute, as evidenced by macro-botanical remains at Su Nuraxi di Barumini and Nuraghe Arrubiu. This approach shifts focus from textual correction to uncovering historical 'fault lines' obscured by imperial rewritings.

Usai, L. (2026). L'Intelligenza Artificiale come Rilevatore di Anomalie Sistemiche nei Testi Classici: Sparagmós Geografico, Anacronismi Stratigrafici e Silencing Informativo tra Filologia Computazionale e Consilienza Archeometrica. Zenodo. https://doi.org/10.5281/ZENODO.23264429