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Plant BiologybioRxiv
Preprint

Research Process Graph: LLM-Driven Extraction and Hierarchical Organization of Research Logic

Jing Yang, Manoj Itharajula, Marek MutwiliD

Abstract

Plant biology now publishes thousands of experimental research articles each year, but their core research logic, namely what questions are being asked, with what methods, and what is being found, remains locked inside free text and invisible to systematic analysis. Here we present a structured, 20-year atlas of The Plant Cell in which every paper is converted into a typed, directed Research Process Graph (RPG) of Question (Q), Method (M) and Finding (F) nodes connected by Q[->]M and M[->]F edges. A benchmarked large language model pipeline applied to 2,633 Plant Cell research articles published 2005-2026 recovered >110,000 Q/M/F nodes and >126,000 directed Q[->]M[->]F chains with>98% precision. A second LLM pass generalises each node into a paper-independent canonical form and assigns it to one of 10 top-level (L1) and [~]90 sub-level (L2) categories for each node type, producing the first comprehensive map of plant-biology research logic at the resolution of individual research questions. The atlas reveals that Plant Cell papers fall into seven canonical paper recipes with characteristic Q[->]M[->]F sub-structures, that peripheral experimental techniques have largely turned over while a stable methodological core persisted, and that the strongest correlate of per-PI citation impact is methodological breadth, not productivity or topical breadth. We release the atlas as a public, browsable database with five complementary interfaces: paper views, an LLM-powered research assistant, expert profiles, a taxonomy browser, and a method explorer. The database, available at https://rpg.connectome.tools/, turns the literature into a queryable community resource.

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