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

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.

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Related Organizations

Agricultural Research Organization
Israel

Keywords

meta-analysis, plant science, systematic review, consensus, large language models, data extraction, automation

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

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