Multi-Model AI Consensus Pipeline for Automated Data Extraction in Meta-Analysis

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

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Authors: Moshe T. Halpern
DOI: 10.5281/zenodo.18670295
Cited by: 0

Abstract

A multi-model AI consensus pipeline for automated quantitative data extraction from scientific research papers for meta-analysis. Uses challenge-aware routing and dual-model extraction (Claude Sonnet 4, Kimi K2.5) with Gemini 3 Flash tiebreaker. Validated against three published meta-analysis datasets with formal TOST equivalence testing.

Fields of Study & Subjects

Meta-analysis and systematic reviews Computational and Text Analysis Methods Advanced Text Analysis Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
17 February 2026
Language
EN