Using distibuctional semantics (word2vec family algorithms and the CADE framework) to learn word embeddings from the Italian literary corpuses we generated.

'Morphological Source Code' functions as a quantized kernel for agentic motility, sharing foundational similarities with a Hilbert Space Kernel. It distinguishes itself by integrating an ADS/CFT-derived, Noetherian topological invariant, facilitating autopoietic automorphisms within a quine-like, epistemologically grounded, QFT-inspired framework.