Colandr vs LitKernel

Colandr is a free web platform for evidence reviews and other document reviews and syntheses. Machine learning ranks citations by relevance to help screen titles and abstracts, while natural language processing classifies included documents into user-defined categories and assists full-text data extraction. Reviewers retain the final inclusion, exclusion, and classification decisions, and teams can collaborate and cross-check work. Citation files can be imported in TXT, RIS, or BIB formats, with a 40 MB limit per import, and screening decisions and extracted data can be exported as CSV. Colandr does not connect directly to citation databases; users export citations elsewhere, although the platform can help create Boolean search strings. Full-text papers must be found and imported individually, with no mass-upload feature. Relevance rankings update after every 10 screened citations, and metadata suggestions begin after 50 hand-coded extractions. Colandr describes itself as open-source and open-access.

LitKernel has no write-up on Specifiction yet; its figures are above.