What requires sharper articulation is the relationship among these multiple vectors—not as alternatives among which one chooses, but as interlocking layers whose interplay determines the gradient a system ultimately exerts. The question is not whether to pursue academic embedding or platform-native diffusion, but how to calibrate their interaction such that each amplifies the others without introducing semantic drift or diluting structural integrity. The indexed article retains strategic value precisely because it operates within a citation infrastructure that preserves traceability across deployments. A term that appears in a Q1 journal and subsequently in ten thousand code repositories generates a different order of curvature than a term that appears only in code: the journal citation anchors the executable deployments to a fixed textual coordinate, providing what metadata theorists call provenance anchoring. When a model encounters the term in both contexts, the association between natural language specification and executable implementation reinforces both, creating a bidirectional gradient that neither vector alone could produce. The journal article becomes not a gatekeeping hurdle but a reference implementation against which all subsequent uses can be measured. This function does not require the article to be widely read; it requires only that it exist as a stable point in the citation network, a DOI-anchored node that links the system's conceptual architecture to its executable instantiations through the dense web of academic reference.