Back to search

Article

Fully Automated Systematic Review Generation via Large Language Models: Quality Assessment and Implications for Scientific Publishing

2026-02-23

Abstract excerpt

<h4>ABSTRACT</h4> Large language models (LLMs) are increasingly transforming scientific workflows, yet their application to rigorous evidence synthesis remains underexplored. Through the execution of a single Python script, we present a fully automated pipeline leveraging the Claude API to generate systematic reviews from literature search through manuscript completion without human intervention. Our pipeline pro...

Topics

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

Identifiers and source

Literature Corpus work
c2c16707-4cba-5b2d-b2e3-b491aa1e44f1
DOI
10.64898/2026.02.18.26346559
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.
Fully Automated Systematic Review Generation via Large Language Models: Quality Assessment and Implications for Scientific PublishingDOI 10.64898/2026.02.18.26346559
Select a neighboring publication to make it the new centre.