ChaokunHong/MetaScreener
AI-powered tool for efficient abstract and PDF screening in systematic reviews.
Employs a multi-LLM ensemble with calibrated confidence aggregation and per-element consensus scoring to route papers to auto-decision or human review based on confidence tiers. Integrates 15+ open-source models via OpenRouter API, features a hierarchical 4-layer screening pipeline combining parallel inference, rule-based filtering, and active learning, with a Vue 3 web UI supporting title/abstract and full-text screening, extraction, and quality assessment workflows.
1,304 stars and 48 monthly downloads. Actively maintained with 226 commits in the last 30 days. Available on PyPI.
Stars
1,304
Forks
47
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 27, 2026
Monthly downloads
48
Commits (30d)
226
Dependencies
22
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