HAWC vs ReviewAid

HAWC is a free web application for storing, displaying, and synthesizing data used in human health and environmental risk assessments. Its modules support study-quality evaluation, data extraction from human epidemiology, animal bioassay, and in vitro studies, evidence synthesis, and dose-response analysis. Assessment teams can assign managers, members, and reviewers role-based permissions for viewing, editing, and administration. Published material is viewable without an account, while collaboration on an ongoing assessment with EPA scientists requires a Login.gov account and approved EPA HAWC group access. Interactive visualizations connect studies, experiments, endpoints, and dose information. Users can download available datasets as Microsoft Excel files and export figures to PDF or other formats. Benchmark dose modeling is performed endpoint by endpoint at the EPA HAWC chemical manager’s discretion. HAWC supports most modern browsers, with Google Chrome preferred, and reports functionality errors with Internet Explorer.

ReviewAid is a free, open-source AI tool for full-text screening and data extraction in systematic reviews. Researchers can provide PICO inclusion and exclusion criteria for classifying papers, then define which fields they want extracted. The tool reports confidence scores and marks low-confidence results for manual review. Downloads are available as CSV, XLSX, or DOCX. ReviewAid supports OpenAI, Anthropic, DeepSeek, Cohere, Z.ai, and local Ollama. When a cloud provider is selected, paper text is sent to that provider for the run; with Ollama, inference takes place on the local machine and the text remains there. The maker says API keys are not stored. Users can work in a browser-based Streamlit app or install locally with Python 3.12 or later and Streamlit on Windows, macOS, or Linux. Hosted sessions may take about 30 seconds to initialize. Submission guidance caps full-text screening at 10 articles and extraction at 20 per submission. ReviewAid is licensed under Apache 2.0 and is described as a supplementary reviewer, not a substitute for manual screening or extraction.