arXiv Artificial Intelligence

MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity

MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity

Quick summary

arXiv:2609.02060v1 Announce Type: new Abstract: 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-sour

Key takeaways

  • arXiv:2609.02060v1 Announce Type: new Abstract: 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.

Why it matters

“MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗