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In this article we introduce a multi-level structural variation approach to the study of a scientific field. The approach is motivated by an explanatory and computational theory of transformative discovery and novel structural variation metrics derived from the theory. We integrate the theoretical framework with a visual analytic process that enables an analyst to study the literature of a scientific field across multiple levels of aggregation and decomposition, including the field as a whole, specialties, topics and predicates. We demonstrate the use of this approach through a study of regenerative medicine.
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Stored only when both papers are in the corpus — 40 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.