MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 22 references that are in the map. First posted on arXiv 2 Sep 2026.
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References · 6
- 2025TurnBench-MS: A Benchmark for Evaluating Multi-Turn, Multi-Step Reasoning in Large Language Modelscited by 12
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- 2025We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrongcited by 3
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- 2026PRISMA: Reinforcement Learning Guided Two-Stage Policy Optimization in Multi-Agent Architecture for Open-Domain Multi-Hop Question Answeringcited by 1
- 2026STIndex: A Context-Aware Multi-Dimensional Spatiotemporal Information Extraction Systemcited by 1
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