Back to search

Article

Operationalising LLM-assisted screening of literature to support systematic reviews

2026-08-03

Abstract excerpt

Large language models (LLMs) can ease the work of screening titles and abstracts for systematic reviews, but obtaining reliable results requires researchers to make practical choices about which LLMs to use, how to combine their scores into a ranking, and how far down that ranking to read. We aimed to identify a general-purpose workflow that screens accurately, minimises human review effort, and generalises across...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
b3db3aa3-38b9-50d0-8705-b80d657d1155
DOI
10.64898/2026.07.29.741127
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Operationalising LLM-assisted screening of literature to support systematic reviewsDOI 10.64898/2026.07.29.741127
LLM-assisted screening and extraction for systematic reviews: workload reduction and refusal-driven missingness in a land-use evidence synthesisSemantic proximity
Human Researchers are Superior to Large Language Models in Writing a Systematic Review in a Comparative Multitask AssessmentSemantic proximity
Sensitivity, specificity and avoidable workload of using a large language models for title and abstract screening in systematic reviews and meta-analysesSemantic proximity
Evaluating Loon Lens Pro™, an AI-Driven Tool for Full-Text Screening in Systematic Reviews: A Validation StudySemantic proximity
Automation of Systematic Reviews with Large Language ModelsSemantic proximity
Prospective validation of NeutrinoReview for LLM-assisted systematic review screening: an indoor air quality case studySemantic proximity
Careful design of Large Language Model pipelines enables expert-level retrieval of evidence-based information from conservation synthesesSemantic proximity
Will generative AI help solve systematic literature reviews? Evidence from a 2-year research programmeSemantic proximity
Fully Automated Systematic Review Generation via Large Language Models: Quality Assessment and Implications for Scientific PublishingSemantic proximity
Assessing the feasibility and acceptability of a bespoke large language model pipeline to extract data from different study designs for public health evidence reviewsSemantic proximity
From Literature to Practice: Application of Large Language Models for Farm Management InsightSemantic proximity
JARVIS, should this study be selected for full-text screening? Performance of a Joint AI-ReViewer Interactive Screening tool for systematic reviewsSemantic proximity
Select a neighboring publication to make it the new centre.