metaScreener: A Plugin-Based Desktop Application for Human-in-the-Loop Systematic Literature Screening

metaScreener is an open-source, cross-platform desktop application implemented inPython/Tkinter that delivers a sequential, multi-stage pipeline for systematic literaturescreening. The software integrates deterministic rule-based filters with largelanguage model (LLM) inference to automate high-volume citation screening withinstructured evidence synthesis workflows. Its plugin architecture exposes seven interoperablemodules covering citation extraction, reference resolution, eligibilitycriteria structuring, heuristic-based filtering, and LLM-based full-record eligibilityadjudication. Each screening decision is logged within a timestamped, SHA-256-verified bundle archive that satisfies the audit and reproducibility requirementsexpected in rigorous evidence synthesis methodology. In a demonstration use casecomprising 776 candidate records, the pipeline reduced the corpus to 73 records requiringfull human review — a 90.6% reduction — with deterministic pre-filteringaccounting for 98.3% of exclusions and LLM-assisted stages providing fine-grainedadjudication over the residual candidate set. Complete decision traceability waspreserved across all stages. metaScreener is released under the MIT licence and ispublicly available at https://github.com/lars-ulaval/metaScreener.