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Systematic reviews are essential for evaluating biomedical treatment options, but the growing size and complexity of the available biomedical literature combined with the rigor of the systematic review method mean that systematic reviews are extremely difficult and labor‐intensive to perform. In this article, I propose a method of searching the literature by systematically mining the various types of citation relationships between articles. I then test the method by comparing its precision and recall to that of 14 published systematic reviews. The method successfully retrieved 74% of the studies included in these reviews and 90% of the studies it could reasonably be expected to retrieve. The method also retrieved fewer than half of the total number of publications retrieved by these reviews and can be performed in substantially less time. This suggests that the proposed method offers a promising complement to traditional text‐based methods of literature identification and retrieval for systematic reviews.
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Stored only when both papers are in the corpus — 62 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.