Abstrackr vs ASReview

Abstrackr is a free web tool for screening citations in systematic reviews. It supports solo work, blinded team screening, pilot rounds, and conflict resolution. After about 100 labels, machine learning ranks remaining citations by predicted relevance. A live PRISMA flow table records screening thresholds, resolved conflicts, exclusion reasons by tag, and analysis of the model’s stop point. Citations can be imported from PubMed, Scopus, or Embase, or uploaded as RIS and CSV files. The service deduplicates records by DOI and PMID and can merge remaining near-duplicates. Results export as CSV or RIS, with a full JSONL download for DuckDB queries. Blinding starts enabled, and changes are logged with user, reason, timestamp, and project snapshots. Member and Leader roles have no stated team-size limit, while reminders arrive 7, 4, and 1 day before deadlines. No installation is needed, and the site directs methodology questions to its community forum.

ASReview is a free, open-source tool that uses AI-aided active learning to prioritize records for systematic review screening, with a human making screening decisions. Its site says the approach can reduce screening workload by up to 95%. Users can simulate AI-aided review to compare models, while Crowdscreen supports parallel screening with access managed by administrators through a private login system. The described model families are ELAS-Ultra, ELAS-Heavy, and language-agnostic ELAS-L; ELAS-Heavy and ELAS-L require the Dory package. ASReview works with reference managers including EndNote and PubMed, and imports and exports CSV, RIS, and XLSX files. Documentation includes a Python API, while the institutional workflow also describes a REST API and CLI for automation. In a local setup, data stays on the user's computer; server deployments keep it in the organization's environment and follow its policies. Support includes documentation, tutorials, videos, community discussion, and organizational workshops and consultancy. ASReview LAB costs nothing with no licensing fees or subscriptions, though running hardware or a server may incur costs.