SOURCE-LINKED INTELLIGENCE
A Large Open Multi-Energy Corpus of Soil Compaction Tests, with Machine-Learning Baselines
Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published correlations rest on one to four hundred specimens, usually from one laboratory at one compactive energy, and are seldom released. This paper releases a corpus without those limits. It holds 2,854 laboratory compaction tests from six public sources, across 162 provenance groups and four Proctor energy levels, with fines from 1.5 to 100%. Every record is audited to the Proctor method its source names, and no energy is inferred. Screening on the zer
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T03:53:13.000Z
First collected: 2026-09-21T05:11:56.580Z. This is not the publication date.