LitCurate：一种配置驱动的AI辅助科学数据库构建框架及在下地幔状态方程数据中的应用
LitCurate: A Configuration-Driven AI-Assisted Framework for Scientific Database Construction with an Application to Lower-Mantle Equation-of-State Data
浏览论文内容
中文总结 AI 辅助
本文提出开源框架LitCurate，整合大语言模型与可审计分阶段工作流构建科学数据库，并将其应用于构建含1334条条目的下地幔高压矿物相状态方程数据库，实现文献到可追溯数据的转化。
中文摘要 AI 辅助
日益增长的科学文献中包含了数十年的实验与计算结果，这些结果本可支撑数据驱动及基于物理的建模，但其中大量信息仍被束缚在出版物中，难以用于大规模分析或科学软件。若需先从海量论文中筛选出相关研究，并提取报告量值时保留足够科学上下文以确保可用性，从文献构建结构化数据库便极具挑战性。本文提出LitCurate，这是一个开源框架，用于通过可审计的分阶段整理工作流，利用大语言模型从文献构建科学数据库。LitCurate整合了文献发现、相关性筛选、全文处理及结构化信息提取，同时保留中间结果与来源，允许研究人员检查和修改各个阶段，而非将自动整理视为黑箱过程。我们将LitCurate应用于构建下地幔及与下地幔相关的高压矿物相的状态方程数据库，该数据库包含205篇论文中的1334条条目。所得数据集将报告的状态方程参数与矿物相、成分、方程形式、方法及参数约束相关联，且在可确定来源时，将值标记为来源报告或引用报告。这些记录可通过可搜索的Web应用程序获取。通过将科学文献与可追溯的机器可读数据相连接，LitCurate提供了一种可重复使用的方法，用于将积累的文献转化为科学分析和计算建模的资源。
英文摘要
The growing scientific literature contains decades of experimental and computational results that could support data-driven and physics-based modeling, yet much of this infor- mation remains locked in publications and is not readily usable for large-scale analysis or sci- entific software. Building structured databases from the literature is particularly challenging whenrelevantstudiesmustfirstbediscoveredamonglargecollectionsofpapersandreported quantities must be extracted with enough scientific context to remain usable. We present LitCurate, an open-source framework for building scientific databases from the literature using large language models within an auditable, stage-wise curation workflow. LitCurate integratesliteraturediscovery, relevancescreening, full-textprocessing, andstructuredinfor- mation extraction while retaining intermediate results and provenance, allowing researchers to inspect and revise individual stages rather than treating automated curation as a black- box process. We apply LitCurate to construct an equation-of-state database of lower-mantle and lower-mantle-relevant high-pressure mineral phases from experimental and theoretical studies, comprising 1,334 entries from 205 papers. The resulting dataset links reported equation-of-state parameters to mineral phases, compositions, equation formulations, meth- ods, and parameter constraints, and labels values as source-reported or citation-reported when provenance can be determined. The records are available through a searchable web application. By connecting scientific literature to traceable, machine-readable data, LitCu- rate provides a reusable approach for transforming accumulated literature into resources for scientific analysis and computational modeling.
