解决可持续性报告中的数据缺口:温室气体排放的基准数据集
Jacob Beck1,2, Anna Steinberg3,4, Andreas Dimmelmeier5
1LMU Munich, Department of Statistics, Munich, 80539, Germany. jacob.beck@lmu.de.
Scientific data
|August 27, 2025
概括
创建可靠的公司温室气体排放数据至关重要. 一个使用人工智能和人类审查的新黄金标准数据集, 提高了气候行动和可持续金融的准确性.
科学领域:
- 环境科学
- 数据科学
- 可持续的金融
背景情况:
- 在减缓气候变化方面,可靠的企业级温室气体 (GHG) 排放数据至关重要.
- 现有的温室气体数据集存在碎片化,不一致和方法不透明,阻碍了可靠的数据采集.
- 迫切需要高质量,透明的排放数据来支持利益相关者.
研究的目的:
- 开发公司级温室气体排放指标的黄金标准数据集.
- 建立一个用于验证和完善自动数据提取模型的基准.
- 促进可持续金融和绿色洗分析的下游应用.
主要方法:
- 通过使用大型语言模型 (LLM) 来自动提取139份可持续性报告中的排放指标.
- 提取的数据经过了两个非专家注释者的独立评估.
- 一个多阶段的审查过程,包括专家评估和面对面的讨论,解决了差异以确保数据质量.
主要成果:
- 一个经过验证的公司温室气体排放指标的黄金标准数据集成功创建.
- 通过结构化的人类-人工智能协作,该方法表明了确保高质量的数据的可靠过程.
- 这一数据集是比较和改进信息提取模型的宝贵资源.
结论:
- 开发的黄金标准数据集显著提高了企业级温室气体排放数据的可靠性.
- 这种LLM提取和严格的人类验证的混合方法为数据质量保证提供了可扩展的解决方案.
- 这种资源广泛适用于气候报告,可持续融资和打击绿色洗.
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