Multiple applications of Reinforced Earth technologies for industrial mining structures – Georgia Pacific Mining design/build project
Bibliographic record
Abstract
Georgia Pacific Mining Canada required expansion of their gypsum mining operation in Nova Scotia, Canada. Herein describes various design-build industrial mining structures using Reinforced Earth® technologies under dynamic and ever-changing surcharge loading conditions. Three separate but inter-connected structures were required to extract the raw materials for the new mining area, namely: 1. Truck Dump MSE Walls and Distribution Slab supporting Cat 773 haul trucks. 2. Surcharge Tunnel with dynamic and fluctuating surface loads applied and 3. Escape Tunnel using MSE walls and concrete roof slabs with heavily loaded spread footing forces applied. All three structures had the added components of conceptual design, final detail design, supply and construct under a “Design-Build” contract. Georgia Pacific Mining Canada required this turnkey project to be in operation for the transition period between the old mining site to the new facilities with guarantees of performance of all structures. The following case history illustrates the flexibility of MSE, TechSpan and the innovative applications of engineering solutions in meeting the needs of a challenging site environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".