让矿产勘探结果可解释，支持自然语言交互查询。
MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity
- 用专家树融合多源地质证据生成可解释的找矿评分
- 在不同测试场景下空间AUC最高达0.917，表现优异
- 适合地质学家和资源勘查人员快速验证新区域潜力
矿产勘探需整合异构的地球化学、地球物理和地质证据，但现有找矿系统常仅提供不透明的分数或热力图。我们提出MineTRACE，一个基于网页的交互式系统，支持铜、金、镍、钨、锡、钴、钽和锰八种矿产的找矿潜力分析。用户可浏览找矿图、查询特定位置或区域，检查支持性证据，并通过自然语言交互获取信息。系统采用由地质知识和已知矿床驱动的透明专家树，将多源证据整合为可解释的找矿评分。对于新位置，对话助手从分析管道中检索评分与支撑证据，并以自然语言呈现。评分器在不同测试场景下的空间AUC最高达0.917；端到端评估则衡量查询准确性和回答可信度。MineTRACE使公开地球科学数据更易获取、理解与验证，助力更高效、透明的矿产勘探。
原文摘要 · Abstract (English)
Mineral exploration requires integrating heterogeneous geochemical, geophysical, and geological evidence, yet existing prospectivity systems often provide only opaque scores or heatmaps. We present MineTRACE, a web-based system for evidence-grounded exploration of eight commodities: Cu, Au, Ni, W, Sn, Co, Ta, and Mn. Users can explore prospectivity maps, query locations or regions, inspect supporting evidence, and interact through natural language. A transparent expert tree, informed by geological knowledge and known deposits, combines multi-source evidence into interpretable prospectivity scores. For a new location, the conversational assistant retrieves the score and supporting evidence from the analysis pipeline and presents them in natural language. The scorer achieves spatial AUC values of up to 0.917 across different test scenarios, while end-to-end evaluation assesses query accuracy and response grounding. MineTRACE makes public geoscience data easier to access, interpret, and verify, supporting more efficient and transparent mineral exploration.
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