Designs machine-learning assisted systematic review workflows. Use for active-learning screening, deduplication, study classification, LLM-assisted extraction, risk-of-bias triage, topic modeling, moderator discovery, and audit logs, while preserving human verification and transparent evidence-synthesis decisions.
Reviews umbrella reviews and second-order meta-analyses. Use when synthesizing existing systematic reviews/meta-analyses, assessing primary-study overlap, duplicate evidence, review quality, AMSTAR/ROBIS-style concerns, discordant conclusions, temporal second-order meta-regression, ecosystem-service trade-offs, and…
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