A geotechnical evaluation of the Cumba Pit Slope Failure, Dominican Republic
Bibliographic record
Abstract
Abstract The combined availability of topographical, geological, structural, hydrogeological and monitoring data is rapidly increasing. Technology and software advances allow the real time incorporation of this data across various software platforms. This paper describes the back-analysis of a 70 m high, pit slope failure of an open pit gold mine in the Dominican Republic, using data from aerial photogrammetry, ground-based synthetic aperture radar and 3D limit equilibrium and finite element modelling. This back-analysis process is considered leading practice with the latest technology. The (northern) side of the Cumba pit slumped along a non-daylighting plane that was identified after the failure event. Remedial investigations included review of geological data, major structures, rock mass constitutive models and groundwater conditions. Topographical and structural data acquired from aerial photogrammetry, pre- and post-failure event, was input into 3D models to replicate observed ground movement. 3D models of pit progression were compared with displacements recorded by ground-based synthetic aperture radar to calibrate model inputs and increase reliability of forward predictions. Such a technical review was completed in less than one week, and the review process implemented for the Cumba pit slope failure now forms the baseline approach for all future geotechnical analysis at the operating mine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".