Using machine learning to advance synthesis and use of conservation and environmental evidence

Abstract

Article impact statement : Machine learning optimizes processes of systematic evidence synthesis and improves its utility for evidence‐based conservation.

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Stored only when both papers are in the corpus — 155 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.