The Δ47 Cognitive Indexing Model (Δ47-CIM) documents an emergent human-internal memory architecture observed during sustained, high-density research workflows involving multiple large language models (LLMs). Rather than relying on linear recall or explicit cataloguing, Δ47-CIM operates through associative anchoring and semantic trigger-based retrieval, functioning analogously to a vector database implemented within human cognition. Developed and observed within the LUMEN Research Framework, the model explains how a human researcher maintains long-term continuity, rapid context reconstruction, and stable navigation across large, disorganised archives and recursive AI interactions. Δ47-CIM formalises six core principles governing this retrieval mechanism and situates them within established cognitive science theories, including semantic networks, spreading activation, and neuroplastic adaptation. This preprint positions Δ47-CIM as the human-side continuity layer in hybrid human–AI systems, with implications for computational cognition, AI governance, extended-mind theory, and the design of user-side alignment and continuity tools