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

arXiv: https://arxiv.org/abs/2609.02060 · HTML: https://mlsanity.com/paper/2609.02060/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 22 references that are in the map.
- First posted on arXiv 2 Sep 2026.

## Builds on (most cited first, 6 of 6)

- [TurnBench-MS: A Benchmark for Evaluating Multi-Turn, Multi-Step Reasoning in Large Language Models](https://mlsanity.com/paper/2506.01341/) (2025)
- [SynJAC: Synthetic-data-driven Joint-granular Adaptation and Calibration for Domain Specific Scanned Document Key Information Extraction](https://mlsanity.com/paper/2410.01609/) (2024)
- [We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrong](https://mlsanity.com/paper/2509.22510/) (2025)
- [Can Argus Judge Them All? Comparing VLMs Across Domains](https://mlsanity.com/paper/2507.01042/) (2025)
- [PRISMA: Reinforcement Learning Guided Two-Stage Policy Optimization in Multi-Agent Architecture for Open-Domain Multi-Hop Question Answering](https://mlsanity.com/paper/2601.05465/) (2026)
- [STIndex: A Context-Aware Multi-Dimensional Spatiotemporal Information Extraction System](https://mlsanity.com/paper/2604.08597/) (2026)

## 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.